Web-Based Traffic Sentiment Analysis Methods and Applications

22/10/201902/07/2019 by admin

In the recent of social media, sentiment analysis has developed rapidly in recent years. However, only a few studies focused on the field of transportation, which failed to meet the stringent requirements of safety, efficiency, and information exchange of intelligent transportation systems (ITSs). We propose the traffic sentiment analysis (TSA) as a new tool to tackle this problem, which provides a new prospective for modern ITSs.

Our methods and models in TSA are proposed in this paper, and the advantages and disadvantages of rule- and learning-based approaches are analyzed based on web data. Practically, we applied the rule-based approach to deal with real problems, presented an architectural design, constructed related bases, demonstrated the process, and discussed the online data collection.

1.2 INTRODUCTION

Transportation systems serve the people in essence, but the modern intelligent transportation systems (ITSs) failed to concern about the public opinions. For the completeness of ITS space, it is necessary to collect and analyze the public wisdom and opinions. With the remarkable advancement of Web 2.0 in the last decade, communication platforms, such as blogs, wikis, online forums, and social-networking groups, have become a rich data-mining source for the detection of public opinions. Therefore, we propose traffic sentiment analysis (TSA) for processing traffic information from websites. As taking consideration of human affection, TSA will enrich the performance of the current ITS space.

TSA is a subfield of sentiment analysis, which concerns about the issues of traffic in particular. Due to the field sensitivity of sentiment analysis, it is necessary to discuss the TSA problems and construct TSA systems specifically. The TSA treats the traffic problems in a new angle, and it supplements the capabilities of current ITS systems. Fig. 1 illustrates the modules of ITS and exhibits that the TSA plays the role of sensing, computing, and supporting the decision making in ITSs.

The functions of the TSA system can be illustrated as follows.

1) Investigation: It is more economical and efficient than the public poll to collect the public opinion through the TSA system.

2) Evaluation: The computational production of the TSA system can be used to evaluate the performance of traffic services and policies.

3) Prediction: The TSA system can be further developed to predict the trends of some social events. For example, to predict whether a cancelled flight would bring chaos, we can analyze the emotion of passengers on their words published on Twitter or Weibo through TSA systems.

In addition, specific parts of the TSA system can be viewed as another form of “social sensors” compared with traditional sensor systems; it can detect the situation from a new humanized perspective. The TSA system is independent of current systems, which is particularly useful in an emergency when other systems were ruined. For example, in 2009, the volcano ash from Iceland caused the malfunction of many cameras in several European countries. In this paper, by constructing a specific TSA system, we addressed the issues and methods in this field and illustrated two cases to demonstrate the value of this research.

Our contribution in this paper can be addressed as follows.

1) We proposed TSA to view the traffic problems in a new perspective.

2) The main issues of TSA applications on web data were discussed based on the web data.

3) The key problems of TSA were addressed, including the design of architecture, the improved rule-based approach, and the construction of related bases.

1.3 LITRATURE SURVEY

CHINESE WORD SEGMENTATION FOR TERRORISM-RELATED CONTENTS

PUBLICATION: D. Zeng, D. Wei, M. Chau, and F. Wang, Intelligence and Security Informatics.New York, NY, USA: Springer-Verlag, 2008, pp. 1–13.

EXPLANATION:

In order to analyze security and terrorism related content in Chinese, it is important to perform word segmentation on Chinese documents. There are many previous studies on Chinese word segmentation. The two major approaches are statistic-based and dictionary-based approaches. The pure statistic methods have lower precision, while the pure dictionary-based method cannot deal with new words and are restricted to the coverage of the dictionary. In this paper, we propose a hybrid method that avoids the limitations of both approaches. Through the use of suffix tree and mutual information (MI) with the dictionary, our segmenter, called IASeg, achieves a high accuracy in word segmentation when domain training is available. It can identify new words through MI-based token merging and dictionary update. In addition, with the Improved Bigram method it can also process N-grams. To evaluate the performance of our segmenter, we compare it with the Hylanda segmenter and the ICTCLAS segmenter using a terrorism-related corpus. The experiment results show that IASeg performs better than the two benchmarks in both precision and recall.

AGENT-BASED CONTROL FOR NETWORKED TRAFFIC MANAGEMENT SYSTEMS

PUBLICATION: F.-Y. Wang, IEEE Intell. Syst., vol. 20, no. 5, pp. 92–96, Sep./Oct. 2005.

EXPLANATION:

Agent or multiagent systems have evolved and diversified rapidly since their inception around the mid 1980s as the key concept and method in distributed artificial intelligence. They have become an established, promising research and application field drawing on and bringing together results and concepts from many disciplines, including AI, computer science, sociology, economics, organization and management science, and philosophy. However, multiagent systems have yet to achieve widespread use for controlling traffic management systems. Most research focuses on developing hierarchical structures, analytical modeling, and optimized algorithms that are effective for real-time traffic applications, as you can see from well-known traffic control systems such as CRONOS, OPAC, SCOOT, SCAT, PRODYN, and RHODES. Although those functional-decomposition-based systems are useful and successful for many traffic management problems, costs and difficulties associated with their development, operation, maintenance, expansion, and upgrading are often prohibitive and sometimes unnecessary, especially in the rapidly arriving age of connectivity. We need to rethink control systems and reinvestigate the use of simple task-oriented agents for traffic control and management of transportation systems.

OPINION FEATURE EXTRACTION USING CLASS SEQUENTIAL RULES

PUBLICATION: M. Hu and B. Liu, presented at the AAAI Spring Symposium Computational

Approaches Analyzing Weblogs, Palo Alto, CA, USA, 2006, Paper AAAI-CAAW-06.

EXPLANATION:

The paper studies the problem of analyzing user comments and reviews of products sold online. Analyzing such reviews and producing a summary of them is very useful to both potential customers and product manufacturers. By analyzing reviews, we mean to extract features of products (also called opinion features) that have been commented by reviewers and determine whether the opinions are positive or negative. This paper focuses on extracting opinion features from Pros and Cons, which typically consist of short phrases or incomplete sentences. We propose a language pattern based approach for this purpose. The language patterns are generated from Class Sequential Rules (CSR). A CSR is different from a classic sequential pattern because a CSR has a fixed class (or target). We propose an algorithm to mine CSR from a set of labeled training sequences. To perform extraction, the mined CSRs are transformed into language patterns, which are used to match Pros and Cons to extract opinion features. Experimental results show that the proposed approach is very effective.

CHAPTER 2

2.0 SYSTEM ANALYSIS

2.1 EXISTING SYSTEM:

Existing approaches to sentiment analysis can be categorized into rule- and learning based approaches. Rule-based approaches often require an expert-defined dictionary of subjective words; this approach predicts the polarity of a sentence or document by analyzing the occurring patterns of such words in text. For example, Wiebe et al. provided a lexicon source of subjectivity clues, such as verbs, adjectives, and nouns, with their polarity (i.e., positive, negative, or neutral) and strength (i.e., strong or weak) annotated. However, this lexicon is able to define the original polarity of a word only, and the actual polarity of a word may be modified by its context in a sentence. Several approaches that consider the context of words have been proposed to determine the sentiment orientation of words.

Previous studies, the data set contains several subjective texts that could not be easily analyzed by the rules. The most typical phenomenon is the ironic sentiment sentences. For instance, in posts regarding fuel prices, the thread title used was “the fuel price will rise,” to which one user replied, “go to sell the car.” Such a reply apparently carries an ironic tone; thus, all annotators manually labeled the reply as “negative.” However, given that the computer cannot detect from the given text any word expressing a negative sentiment, the methods cannot recognize the sentiment polarity. Therefore, numerous problems remain unsolved.

2.1.1 DISADVANTAGES:

Rule-based approach, the disadvantage is that the sentiment polarity results cannot be as precise as expected if the context of the texts is not considered. Nevertheless, for handling web data, this type of approach has the following advantages.

The precision of the rule-based approach is independent of the sizes of the clauses. Second, the syntax rule of a certain language is basic and static despite the differences in the stylistic features of various users. The thought process and word choice basically remain unchanged.

Existing the rules of the rule-based approach is relatively static in the rule-based approach can be easily extended by simply updating the sentiment lexicon, although new sentimental words rapidly emerge and the sentiment of several words may be changed with words.

2.2 PROPOSED SYSTEM:

We propose traffic sentiment analysis (TSA) for processing traffic information from websites. As taking consideration of human affection, TSA will enrich the performance of the current ITS space. TSA is a subfield of sentiment analysis, which concerns about the issues of traffic in articular. Due to the field sensitivity of sentiment analysis, it is necessary to discuss the TSA problems and construct TSA systems specifically.

The TSA treats the traffic problems in a new angle, and it supplements the capabilities of current ITS systems in the modules of ITS and exhibits that the TSA plays the role of sensing, computing, and supporting the decision making in ITSs. The functions of the TSA system can be illustrated as follows. 1) Investigation: It is more economical and efficient than the public poll to collect the public opinion through the TSA system. 2) Evaluation: The computational production of the TSA system can be used to evaluate the performance of traffic services and policies. 3) Prediction: The TSA system can be further developed to predict the trends of some social events.

For example, to predict whether a cancelled flight would bring chaos, we can analyze the emotion of passengers on their words published on Twitter or Weibo through TSA systems. In addition, specific parts of the TSA system can be viewed as another form of “social sensors” compared with traditional sensor systems; it can detect the situation from a new humanized perspective.

2.2.1 ADVANTAGES:

We approach is adopted here to address the distinct challenges posed by the web data set illustrated the architecture of TSA; the architecture is based on the tackling process; and its main components, including 1) web data collection, 2) preprocessing, 3) extraction of subjects and objects, 4) extraction of sentiment properties, 5) sentiment calculation and classification, 6) evaluation or applications, and 7) feed-back, improve the construction of the sentiment, rule, and TSA object bases.

Data collection: We gathered data from several websites, such ensuring that the conclusions are definitely based on public opinion or, at least, represent part of the public opinion.

Preprocessing: As previously mentioned, web documents must be processed additionally because that segment words by spaces in sentences. In the preprocessing, the following steps are included: 1) the segmentation of text, 2) the labeling of words, and 3) the replacement of synonymous expressions.

2.3 HARDWARE & SOFTWARE REQUIREMENTS:

2.3.1 HARDWARE REQUIREMENT:

v Processor – Pentium –IV

Speed – 1.1 GHz
- RAM – 256 MB (min)
- Hard Disk – 20 GB
- Floppy Drive – 1.44 MB
- Key Board – Standard Windows Keyboard
- Mouse – Two or Three Button Mouse
- Monitor – SVGA

2.3.2 SOFTWARE REQUIREMENTS:

Operating System : Windows XP or Win7
Front End : JAVA JDK 1.7
Back End : MS ACCESS 2007
Tools : Netbeans 7
Document : MS-Office 2007

CHAPTER 3

3.0 SYSTEM DESIGN:

Data Flow Diagram / Use Case Diagram / Flow Diagram:

The DFD is also called as bubble chart. It is a simple graphical formalism that can be used to represent a system in terms of the input data to the system, various processing carried out on these data, and the output data is generated by the system

The data flow diagram (DFD) is one of the most important modeling tools. It is used to model the system components. These components are the system process, the data used by the process, an external entity that interacts with the system and the information flows in the system.

DFD shows how the information moves through the system and how it is modified by a series of transformations. It is a graphical technique that depicts information flow and the transformations that are applied as data moves from input to output.

DFD is also known as bubble chart. A DFD may be used to represent a system at any level of abstraction. DFD may be partitioned into levels that represent increasing information flow and functional detail.

NOTATION:

SOURCE OR DESTINATION OF DATA:

External sources or destinations, which may be people or organizations or other entities

DATA SOURCE:

Here the data referenced by a process is stored and retrieved.

PROCESS:

People, procedures or devices that produce data’s in the physical component is not identified.

DATA FLOW:

Data moves in a specific direction from an origin to a destination. The data flow is a “packet” of data.

MODELING RULES:

There are several common modeling rules when creating DFDs:

All processes must have at least one data flow in and one data flow out.
All processes should modify the incoming data, producing new forms of outgoing data.
Each data store must be involved with at least one data flow.
Each external entity must be involved with at least one data flow.
A data flow must be attached to at least one process.

3.1 ARCHITECTURE DIAGRAM

3.2 DATAFLOW DIAGRAM

UML DIAGRAMS:

3.2 USE CASE DIAGRAM:

3.3 CLASS DIAGRAM:

3.4 SEQUENCE DIAGRAM:

3.5 ACTIVITY DIAGRAM:

CHAPTER 4

4.0 IMPLEMENTATION:

TSA ARCHITECTURE

Previous studies on Chinese texts have devoted considerable efforts on architectural design. Che et al. designed the architecture of the language technology platform (LTP), an integrated Chinese processing platform including a suite of high-performance natural language processing (NLP) modules and relevant corpora. They achieved plausible results in several relevant evaluations, particularly for syntactic and semantic parsing modules. Li et al. designed the architecture of sentiment analysis application in the financial domain on the basis of morphemes. A rule-based approach is adopted here to address the distinct challenges posed by the Chinese data set. Fig. 2 illustrated the architecture of TSA; the architecture is based on the tackling process; and its main components, including 1) web data collection, 2) preprocessing, 3) extraction of subjects and objects, 4) extraction of sentiment properties, 5) sentiment calculation and classification, 6) evaluation or applications, and 7) feed- back, improve the construction of the sentiment, rule, and TSA object bases.

Data collection: To address the problem, we gathered data from several websites, such as Sina Weibo, Tencent Weibo, Tianya, and autohome (the upper block in Fig. 2), ensuring that the conclusions are definitely based on public opinion or, at least, represent part of the public opinion details of data collection are discussed in Section V.

Preprocessing: As previously mentioned, Chinese documents must be processed additionally because that Chinese language does not segment words by spaces in sentences. In the preprocessing, the following steps are included: 1) the segmentation of text, 2) the labeling of words, and 3) the replacement of synonymous expressions. The first two steps are done by a Chinese segmentation tool; we employ the Chinese Lexical Analysis System 3 launched by the social media, various expressions denote the same meaning. For example, several users commonly use “d,” which represents the Chinese character “ ” (support), to express agreement with others. Therefore, the replacement of synonymous expressions (step 3) is necessary to reduce the complexity and increase the precision of following processes.

Word segmentation optimization: To avoid unnecessary disturbances and improve precision, preprocessing should be conducted according to the material and the demand of the algorithms. However, in practice, the result of word segmentation in Chinese is far from expected. In some cases, this step may even reduce the precision. For example, “” is separated as ( /n). In fact, “ ” is an abbreviation of a company name, which represents one of the two Chinese oil giants. Therefore, it is necessary to improve the performance of the Chinese segmentation. In this paper, we propose to construct the “sentiment base” in the application of TSA. In practice, the “sentiment base” consists of the TSA sentiment base and HowNet (subsection B).

Extraction of subjects and objects: Subjects and objects are mainly extracted by context mining and document analysis. In TSA, appropriate models should be designed in context mining according to different data sets and resources. Context mining should obtain results as efficiently as possible to provide the necessary background knowledge for the subsequent steps. In practice, context mining includes conservation extraction and coreference analysis. Conservation extraction refers to handling the text, such as “citation, @.” In addition, coreference analysis refers to mining the object represented by other words. For example, the address in Sina Weibo is usually represented by a hyperlink.

4.1 ALGORITHM

In this paper, we propose to construct the sentiment, modifier, object, and rule bases. Assume that the sentiment polarity of a word is determined by its morphemes. If the morphemes of a word appear in the positive lexicon more frequently than they do in the negative lexicon, the word is positive; otherwise, the word is negative. To measure the positive and negative tendencies of the morpheme q, we assign positive and negative weights to the morphemes as follows:

In formula (3), the polarity Sci depends on morphemes Ci, and the absolute value of Sci is the degree of tendency of morphemes Ci. The steps for calculating the sentiment polarity of words are as follows. Scan the positive and negative word lexicons; if the word w appears in the positive word lexicon, Sw = 1; if the word appears in the negative word lexicon, Sw = −1. Otherwise, the sentiment polarity is computed using morphemes by

Where Sw represents the sentiment polarity of the word w, which consists of c1, c2, . . . , cp. If Sw > 0, the sentiment polarity of the word is positive; otherwise, the sentiment polarity of the word is negative. If the value obtained is close to zero, the word can be considered neutral.

4.2 MODULES:

DATA COLLECTION TSA:

IT’S TRANSPORT SYSTEMS:

RULE BASED APPROACH:

TSA ANALYTICAL TECHNIQUE:

4.3 MODULE DESCRIPTION:

DATA COLLECTION TSA:

Information regarding traffic on the Web can be classified

into three categories. The first category consists of news, expert

commentaries, announcements, etc., from the traffic website.

The second includes posts from the transport sector in forums.

These forums provide a platform through which users

can exchange information about social topics, such as traffic

congestions and transportation policies. The third includes realtime

information about traffic in microblogging, which can be

found from the social media, such as weibo.com. The sentiment

polarity of the first category is not easily distinguished, but its

content is true and meaningful. The sentiment polarity of the

second category is clear, and usually, a discussion on certain

events or topics may be highly valuable for tracking public

opinion. The third category, which includes real-time traffic

information, may not have a fixed topic but often located in a

certain place. Such information bears significance for obtaining

real-time information of travelers and creating a backup sensor

network system. Data from the specific websites can be collected by the open

application programming interface or correspondent crawler,

such as the first and third categories of information. However,

collecting a data set on a specific topic is more difficult. In most

forums, the information-publishing platform can be divided

into a series of boards containing various categories or topics. In

a predefined subject board, the topics are designed for specific

events, providing a relatively better framework for the readers

and commenters. Nevertheless, the categorization is too simple

and indistinct for analysis and research because of the following

reasons: 1) not all topics can be mapped to a single board; 2) the

contents of the post are not strictly related to the object topics;

and 3) a board of forum often contains more than one topic.

Therefore, to precisely collect a topic line and gather the

information to one post, we first design a special crawler by

using depth retrieval. Traffic-related terms are adopted to build

the key ontological vocabulary used for the built-in search

engine of the website.

IT’S TRANSPORT SYSTEMS:

The advances in cloud computing and internet of things (IoT) have provided a promising opportunity to further address the increasing transportation issues, such as heavy traffic, congestion, and vehicle safety. In the past few years, researchers have proposed a few models that use cloud computing for implementing intelligent transportation systems (ITSs). For example, a new vehicular cloud architecture called ITS-Cloud was proposed to improve vehicle-to-vehicle communication and road safety A cloud-based urban traffic control system was proposed to optimize traffic control a service-oriented architecture (SOA), this system uses a number of software services (SaaS), such as intersection control services, area management service, cloud service discovery service, and sensor service, to perform different tasks.

These services also interact with each other to exchange information and provide a solid basis for building a collaborative traffic control and processing system in a distributed cloud environment. As an emerging technology caused by rapid advances in modern wireless telecommunication, IoT has received a lot of attention and is expected to bring benefits to numerous application areas including health care, manufacturing, and transportation. Currently, the use of IoT in transportation is still in its early stage and most research on ITSs has not leveraged the IoT technology as a solution or an enabling infrastructure.

We propose to use both cloud computing and IoT as an enabling infrastructure for developing a vehicular data cloud platform where transportation-related information, such as traffic control and management, car location tracking and monitoring, road condition, car warranty, and maintenance information, can be intelligently connected and made available to drivers, automakers, part-manufacturer, vehicle quality controller, safety authorities, and regional transportation division. An experiment of using data mining models to analyze vehicular data clouds in the IoT environment was also conducted to demonstrate the feasibility of vehicular data mining service.

RULE BASED APPROACH:

Rule-based approach is needed, e.g., whether a noun that could represent the sentiment of the texts exists. As emphasized in previous studies, the data set contains several subjective texts that could not be easily analyzed by the rules. The most typical phenomenon is the ironic sentiment sentences. For instance, in posts regarding fuel prices, the thread title used was “the fuel price will rise,” to which one user replied, “go to sell the car.” Such a reply apparently carries an ironic tone; thus, all annotators manually labeled the reply as “negative.” However, given that the computer cannot detect from the given text any word expressing a negative sentiment, the methods cannot recognize the sentiment polarity. Therefore, numerous problems remain unsolved. For the limitations of the existing lexicons, an improved lexicon should be developed, which requires long-term and arduous efforts. We proposed the construction of ITSs under the architecture of artificial, computational, and parallel (ACP) methods, with the TSA system as one of the data sources.

TSA ANALYTICAL TECHNIQUE:

Text sentiment calculation can be categorized into three levels, namely, word, sentence, and document levels. The calculation of the sentiment polarity of words is a basic step in the construction of the sentiment word base. In practice, we consider the words or phrases as another form of sentence. Therefore, text processing includes two main parts, the polarity calculation of the sentence- and document-level text. Fig. 3 shows the overall process involved in the proposed approach. The method includes two major steps, i.e., the sentence sentiment analysis and document sentiment aggregation. Considering the subtlety of Chinese expression, we first decompose a document into constituting sentences and determine the sentiment polarity of each sentence. In contrast to early document-level analytical approaches we regard sentences as atomic units for semantic analysis. The polarity scores of all the sentences are subsequently synthesized to compute for the overall polarity of the entire document. The sentiment polarity of a sentence is defined as ps. ps is determined to extract the SND patterns and calculate the sentiment polarity score according to the SND patterns identified in the text.

CHAPTER 5

5.0 SYSTEM STUDY:

5.1 FEASIBILITY STUDY:

The feasibility of the project is analyzed in this phase and business proposal is put forth with a very general plan for the project and some cost estimates. During system analysis the feasibility study of the proposed system is to be carried out. This is to ensure that the proposed system is not a burden to the company. For feasibility analysis, some understanding of the major requirements for the system is essential.

Three key considerations involved in the feasibility analysis are

ECONOMICAL FEASIBILITY
TECHNICAL FEASIBILITY
SOCIAL FEASIBILITY

5.1.1 ECONOMICAL FEASIBILITY:

This study is carried out to check the economic impact that the system will have on the organization. The amount of fund that the company can pour into the research and development of the system is limited. The expenditures must be justified. Thus the developed system as well within the budget and this was achieved because most of the technologies used are freely available. Only the customized products had to be purchased.

5.1.2 TECHNICAL FEASIBILITY

This study is carried out to check the technical feasibility, that is, the technical requirements of the system. Any system developed must not have a high demand on the available technical resources. This will lead to high demands on the available technical resources. This will lead to high demands being placed on the client. The developed system must have a modest requirement, as only minimal or null changes are required for implementing this system.

5.1.3 SOCIAL FEASIBILITY:

The aspect of study is to check the level of acceptance of the system by the user. This includes the process of training the user to use the system efficiently. The user must not feel threatened by the system, instead must accept it as a necessity. The level of acceptance by the users solely depends on the methods that are employed to educate the user about the system and to make him familiar with it. His level of confidence must be raised so that he is also able to make some constructive criticism, which is welcomed, as he is the final user of the system.

5.2 SYSTEM TESTING:

This creates two problems, the time lag between the cause and the appearance of the problem and the effect of the system errors on the files and records within the system. A small system error can conceivably explode into a much larger Problem. Effective testing early in the purpose translates directly into long term cost savings from a reduced number of errors. Another reason for system testing is its utility, as a user-oriented vehicle before implementation. The best programs are worthless if it produces the correct outputs.

5.2.1 UNIT TESTING:

Description	Expected result
Test for application window properties.	All the properties of the windows are to be properly aligned and displayed.
Test for mouse operations.	All the mouse operations like click, drag, etc. must perform the necessary operations without any exceptions.

A program represents the logical elements of a system. For a program to run satisfactorily, it must compile and test data correctly and tie in properly with other programs. Achieving an error free program is the responsibility of the programmer. Program testing checks for two types of errors: syntax and logical. Syntax error is a program statement that violates one or more rules of the language in which it is written. An improperly defined field dimension or omitted keywords are common syntax errors. These errors are shown through error message generated by the computer. For Logic errors the programmer must examine the output carefully.

5.1.2 FUNCTIONAL TESTING:

Functional testing of an application is used to prove the application delivers correct results, using enough inputs to give an adequate level of confidence that will work correctly for all sets of inputs. The functional testing will need to prove that the application works for each client type and that personalization function work correctly.When a program is tested, the actual output is compared with the expected output. When there is a discrepancy the sequence of instructions must be traced to determine the problem. The process is facilitated by breaking the program into self-contained portions, each of which can be checked at certain key points. The idea is to compare program values against desk-calculated values to isolate the problems.

Description	Expected result
Test for all modules.	All peers should communicate in the group.
Test for various peer in a distributed network framework as it display all users available in the group.	The result after execution should give the accurate result.

5.1. 3 NON-FUNCTIONAL TESTING:

The Non Functional software testing encompasses a rich spectrum of testing strategies, describing the expected results for every test case. It uses symbolic analysis techniques. This testing used to check that an application will work in the operational environment. Non-functional testing includes:

Load testing
Performance testing
Usability testing
Reliability testing
Security testing

5.1.4 LOAD TESTING:

An important tool for implementing system tests is a Load generator. A Load generator is essential for testing quality requirements such as performance and stress. A load can be a real load, that is, the system can be put under test to real usage by having actual telephone users connected to it. They will generate test input data for system test.

Description	Expected result
It is necessary to ascertain that the application behaves correctly under loads when ‘Server busy’ response is received.	Should designate another active node as a Server.

5.1.5 PERFORMANCE TESTING:

Performance tests are utilized in order to determine the widely defined performance of the software system such as execution time associated with various parts of the code, response time and device utilization. The intent of this testing is to identify weak points of the software system and quantify its shortcomings.

Description	Expected result
This is required to assure that an application perforce adequately, having the capability to handle many peers, delivering its results in expected time and using an acceptable level of resource and it is an aspect of operational management.	Should handle large input values, and produce accurate result in a expected time.

5.1.6 RELIABILITY TESTING:

The software reliability is the ability of a system or component to perform its required functions under stated conditions for a specified period of time and it is being ensured in this testing. Reliability can be expressed as the ability of the software to reveal defects under testing conditions, according to the specified requirements. It the portability that a software system will operate without failure under given conditions for a given time interval and it focuses on the behavior of the software element. It forms a part of the software quality control team.

Description	Expected result
This is to check that the server is rugged and reliable and can handle the failure of any of the components involved in provide the application.	In case of failure of the server an alternate server should take over the job.

5.1.7 SECURITY TESTING:

Security testing evaluates system characteristics that relate to the availability, integrity and confidentiality of the system data and services. Users/Clients should be encouraged to make sure their security needs are very clearly known at requirements time, so that the security issues can be addressed by the designers and testers.

Description	Expected result
Checking that the user identification is authenticated.	In case failure it should not be connected in the framework.
Check whether group keys in a tree are shared by all peers.	The peers should know group key in the same group.

5.1.8 WHITE BOX TESTING:

White box testing, sometimes called glass-box testing is a test case design method that uses the control structure of the procedural design to derive test cases. Using white box testing method, the software engineer can derive test cases. The White box testing focuses on the inner structure of the software structure to be tested.

Description	Expected result
Exercise all logical decisions on their true and false sides.	All the logical decisions must be valid.
Execute all loops at their boundaries and within their operational bounds.	All the loops must be finite.
Exercise internal data structures to ensure their validity.	All the data structures must be valid.

5.1.9 BLACK BOX TESTING:

Black box testing, also called behavioral testing, focuses on the functional requirements of the software. That is, black testing enables the software engineer to derive sets of input conditions that will fully exercise all functional requirements for a program. Black box testing is not alternative to white box techniques. Rather it is a complementary approach that is likely to uncover a different class of errors than white box methods. Black box testing attempts to find errors which focuses on inputs, outputs, and principle function of a software module. The starting point of the black box testing is either a specification or code. The contents of the box are hidden and the stimulated software should produce the desired results.

Description	Expected result
To check for incorrect or missing functions.	All the functions must be valid.
To check for interface errors.	The entire interface must function normally.
To check for errors in a data structures or external data base access.	The database updation and retrieval must be done.
To check for initialization and termination errors.	All the functions and data structures must be initialized properly and terminated normally.

All the above system testing strategies are carried out in as the development, documentation and institutionalization of the proposed goals and related policies is essential.

CHAPTER 6

6.0 SOFTWARE DESCRIPTION:

6.1 JAVA TECHNOLOGY:

Java technology is both a programming language and a platform.

The Java Programming Language

The Java programming language is a high-level language that can be characterized by all of the following buzzwords:

Simple
- Architecture neutral
- Object oriented
- Portable
- Distributed
- High performance
- Interpreted
- Multithreaded
- Robust
- Dynamic
- Secure

With most programming languages, you either compile or interpret a program so that you can run it on your computer. The Java programming language is unusual in that a program is both compiled and interpreted. With the compiler, first you translate a program into an intermediate language called Java byte codes —the platform-independent codes interpreted by the interpreter on the Java platform. The interpreter parses and runs each Java byte code instruction on the computer. Compilation happens just once; interpretation occurs each time the program is executed. The following figure illustrates how this works.

You can think of Java byte codes as the machine code instructions for the Java Virtual Machine (Java VM). Every Java interpreter, whether it’s a development tool or a Web browser that can run applets, is an implementation of the Java VM. Java byte codes help make “write once, run anywhere” possible. You can compile your program into byte codes on any platform that has a Java compiler. The byte codes can then be run on any implementation of the Java VM. That means that as long as a computer has a Java VM, the same program written in the Java programming language can run on Windows 2000, a Solaris workstation, or on an iMac.

6.2 THE JAVA PLATFORM:

A platform is the hardware or software environment in which a program runs. We’ve already mentioned some of the most popular platforms like Windows 2000, Linux, Solaris, and MacOS. Most platforms can be described as a combination of the operating system and hardware. The Java platform differs from most other platforms in that it’s a software-only platform that runs on top of other hardware-based platforms.

The Java platform has two components:

The Java Virtual Machine (Java VM)
The Java Application Programming Interface (Java API)

You’ve already been introduced to the Java VM. It’s the base for the Java platform and is ported onto various hardware-based platforms.

The Java API is a large collection of ready-made software components that provide many useful capabilities, such as graphical user interface (GUI) widgets. The Java API is grouped into libraries of related classes and interfaces; these libraries are known as packages. The next section, What Can Java Technology Do? Highlights what functionality some of the packages in the Java API provide.

The following figure depicts a program that’s running on the Java platform. As the figure shows, the Java API and the virtual machine insulate the program from the hardware.

Native code is code that after you compile it, the compiled code runs on a specific hardware platform. As a platform-independent environment, the Java platform can be a bit slower than native code. However, smart compilers, well-tuned interpreters, and just-in-time byte code compilers can bring performance close to that of native code without threatening portability.

6.3 WHAT CAN JAVA TECHNOLOGY DO?

The most common types of programs written in the Java programming language are applets and applications. If you’ve surfed the Web, you’re probably already familiar with applets. An applet is a program that adheres to certain conventions that allow it to run within a Java-enabled browser.

However, the Java programming language is not just for writing cute, entertaining applets for the Web. The general-purpose, high-level Java programming language is also a powerful software platform. Using the generous API, you can write many types of programs.

An application is a standalone program that runs directly on the Java platform. A special kind of application known as a server serves and supports clients on a network. Examples of servers are Web servers, proxy servers, mail servers, and print servers. Another specialized program is a servlet.

A servlet can almost be thought of as an applet that runs on the server side. Java Servlets are a popular choice for building interactive web applications, replacing the use of CGI scripts. Servlets are similar to applets in that they are runtime extensions of applications. Instead of working in browsers, though, servlets run within Java Web servers, configuring or tailoring the server.

How does the API support all these kinds of programs? It does so with packages of software components that provides a wide range of functionality. Every full implementation of the Java platform gives you the following features:

The essentials: Objects, strings, threads, numbers, input and output, data structures, system properties, date and time, and so on.
Applets: The set of conventions used by applets.
Networking: URLs, TCP (Transmission Control Protocol), UDP (User Data gram Protocol) sockets, and IP (Internet Protocol) addresses.
Internationalization: Help for writing programs that can be localized for users worldwide. Programs can automatically adapt to specific locales and be displayed in the appropriate language.
Security: Both low level and high level, including electronic signatures, public and private key management, access control, and certificates.
Software components: Known as JavaBeans^TM, can plug into existing component architectures.
Object serialization: Allows lightweight persistence and communication via Remote Method Invocation (RMI).
Java Database Connectivity (JDBC^TM): Provides uniform access to a wide range of relational databases.

The Java platform also has APIs for 2D and 3D graphics, accessibility, servers, collaboration, telephony, speech, animation, and more. The following figure depicts what is included in the Java 2 SDK.

6.4 HOW WILL JAVA TECHNOLOGY CHANGE MY LIFE?

We can’t promise you fame, fortune, or even a job if you learn the Java programming language. Still, it is likely to make your programs better and requires less effort than other languages. We believe that Java technology will help you do the following:

Get started quickly: Although the Java programming language is a powerful object-oriented language, it’s easy to learn, especially for programmers already familiar with C or C++.
Write less code: Comparisons of program metrics (class counts, method counts, and so on) suggest that a program written in the Java programming language can be four times smaller than the same program in C++.
Write better code: The Java programming language encourages good coding practices, and its garbage collection helps you avoid memory leaks. Its object orientation, its JavaBeans component architecture, and its wide-ranging, easily extendible API let you reuse other people’s tested code and introduce fewer bugs.
Develop programs more quickly: Your development time may be as much as twice as fast versus writing the same program in C++. Why? You write fewer lines of code and it is a simpler programming language than C++.
Avoid platform dependencies with 100% Pure Java: You can keep your program portable by avoiding the use of libraries written in other languages. The 100% Pure Java^TMProduct Certification Program has a repository of historical process manuals, white papers, brochures, and similar materials online.
Write once, run anywhere: Because 100% Pure Java programs are compiled into machine-independent byte codes, they run consistently on any Java platform.
Distribute software more easily: You can upgrade applets easily from a central server. Applets take advantage of the feature of allowing new classes to be loaded “on the fly,” without recompiling the entire program.

6.5 ODBC:

Microsoft Open Database Connectivity (ODBC) is a standard programming interface for application developers and database systems providers. Before ODBC became a de facto standard for Windows programs to interface with database systems, programmers had to use proprietary languages for each database they wanted to connect to. Now, ODBC has made the choice of the database system almost irrelevant from a coding perspective, which is as it should be. Application developers have much more important things to worry about than the syntax that is needed to port their program from one database to another when business needs suddenly change.

Through the ODBC Administrator in Control Panel, you can specify the particular database that is associated with a data source that an ODBC application program is written to use. Think of an ODBC data source as a door with a name on it. Each door will lead you to a particular database. For example, the data source named Sales Figures might be a SQL Server database, whereas the Accounts Payable data source could refer to an Access database. The physical database referred to by a data source can reside anywhere on the LAN.

The ODBC system files are not installed on your system by Windows 95. Rather, they are installed when you setup a separate database application, such as SQL Server Client or Visual Basic 4.0. When the ODBC icon is installed in Control Panel, it uses a file called ODBCINST.DLL. It is also possible to administer your ODBC data sources through a stand-alone program called ODBCADM.EXE. There is a 16-bit and a 32-bit version of this program and each maintains a separate list of ODBC data sources.

From a programming perspective, the beauty of ODBC is that the application can be written to use the same set of function calls to interface with any data source, regardless of the database vendor. The source code of the application doesn’t change whether it talks to Oracle or SQL Server. We only mention these two as an example. There are ODBC drivers available for several dozen popular database systems. Even Excel spreadsheets and plain text files can be turned into data sources. The operating system uses the Registry information written by ODBC Administrator to determine which low-level ODBC drivers are needed to talk to the data source (such as the interface to Oracle or SQL Server). The loading of the ODBC drivers is transparent to the ODBC application program. In a client/server environment, the ODBC API even handles many of the network issues for the application programmer.

The advantages of this scheme are so numerous that you are probably thinking there must be some catch. The only disadvantage of ODBC is that it isn’t as efficient as talking directly to the native database interface. ODBC has had many detractors make the charge that it is too slow. Microsoft has always claimed that the critical factor in performance is the quality of the driver software that is used. In our humble opinion, this is true. The availability of good ODBC drivers has improved a great deal recently. And anyway, the criticism about performance is somewhat analogous to those who said that compilers would never match the speed of pure assembly language. Maybe not, but the compiler (or ODBC) gives you the opportunity to write cleaner programs, which means you finish sooner. Meanwhile, computers get faster every year.

6.6 JDBC:

In an effort to set an independent database standard API for Java; Sun Microsystems developed Java Database Connectivity, or JDBC. JDBC offers a generic SQL database access mechanism that provides a consistent interface to a variety of RDBMSs. This consistent interface is achieved through the use of “plug-in” database connectivity modules, or drivers. If a database vendor wishes to have JDBC support, he or she must provide the driver for each platform that the database and Java run on.

To gain a wider acceptance of JDBC, Sun based JDBC’s framework on ODBC. As you discovered earlier in this chapter, ODBC has widespread support on a variety of platforms. Basing JDBC on ODBC will allow vendors to bring JDBC drivers to market much faster than developing a completely new connectivity solution.

JDBC was announced in March of 1996. It was released for a 90 day public review that ended June 8, 1996. Because of user input, the final JDBC v1.0 specification was released soon after.

The remainder of this section will cover enough information about JDBC for you to know what it is about and how to use it effectively. This is by no means a complete overview of JDBC. That would fill an entire book.

6.7 JDBC Goals:

Few software packages are designed without goals in mind. JDBC is one that, because of its many goals, drove the development of the API. These goals, in conjunction with early reviewer feedback, have finalized the JDBC class library into a solid framework for building database applications in Java.

The goals that were set for JDBC are important. They will give you some insight as to why certain classes and functionalities behave the way they do. The eight design goals for JDBC are as follows:

SQL Level API

The designers felt that their main goal was to define a SQL interface for Java. Although not the lowest database interface level possible, it is at a low enough level for higher-level tools and APIs to be created. Conversely, it is at a high enough level for application programmers to use it confidently. Attaining this goal allows for future tool vendors to “generate” JDBC code and to hide many of JDBC’s complexities from the end user.

SQL Conformance

SQL syntax varies as you move from database vendor to database vendor. In an effort to support a wide variety of vendors, JDBC will allow any query statement to be passed through it to the underlying database driver. This allows the connectivity module to handle non-standard functionality in a manner that is suitable for its users.

JDBC must be implemental on top of common database interfaces

The JDBC SQL API must “sit” on top of other common SQL level APIs. This goal allows JDBC to use existing ODBC level drivers by the use of a software interface. This interface would translate JDBC calls to ODBC and vice versa.

Provide a Java interface that is consistent with the rest of the Java system

Because of Java’s acceptance in the user community thus far, the designers feel that they should not stray from the current design of the core Java system.

Keep it simple

This goal probably appears in all software design goal listings. JDBC is no exception. Sun felt that the design of JDBC should be very simple, allowing for only one method of completing a task per mechanism. Allowing duplicate functionality only serves to confuse the users of the API.

Use strong, static typing wherever possible

Strong typing allows for more error checking to be done at compile time; also, less error appear at runtime.

Keep the common cases simple

Because more often than not, the usual SQL calls used by the programmer are simple SELECT’s, INSERT’s, DELETE’s and UPDATE’s, these queries should be simple to perform with JDBC. However, more complex SQL statements should also be possible.

Finally we decided to precede the implementation using Java Networking.

And for dynamically updating the cache table we go for MS Access database.

Java ha two things: a programming language and a platform.

Java is a high-level programming language that is all of the following

Simple Architecture-neutral

Object-oriented Portable

Distributed High-performance

Interpreted Multithreaded

Robust Dynamic Secure

Java is also unusual in that each Java program is both compiled and interpreted. With a compile you translate a Java program into an intermediate language called Java byte codes the platform-independent code instruction is passed and run on the computer.

Compilation happens just once; interpretation occurs each time the program is executed. The figure illustrates how this works.

6.7 NETWORKING TCP/IP STACK:

The TCP/IP stack is shorter than the OSI one:

TCP is a connection-oriented protocol; UDP (User Datagram Protocol) is a connectionless protocol.

IP datagram’s:

The IP layer provides a connectionless and unreliable delivery system. It considers each datagram independently of the others. Any association between datagram must be supplied by the higher layers. The IP layer supplies a checksum that includes its own header. The header includes the source and destination addresses. The IP layer handles routing through an Internet. It is also responsible for breaking up large datagram into smaller ones for transmission and reassembling them at the other end.

UDP:

UDP is also connectionless and unreliable. What it adds to IP is a checksum for the contents of the datagram and port numbers. These are used to give a client/server model – see later.

TCP:

TCP supplies logic to give a reliable connection-oriented protocol above IP. It provides a virtual circuit that two processes can use to communicate.

Internet addresses

In order to use a service, you must be able to find it. The Internet uses an address scheme for machines so that they can be located. The address is a 32 bit integer which gives the IP address.

Network address:

Class A uses 8 bits for the network address with 24 bits left over for other addressing. Class B uses 16 bit network addressing. Class C uses 24 bit network addressing and class D uses all 32.

Subnet address:

Internally, the UNIX network is divided into sub networks. Building 11 is currently on one sub network and uses 10-bit addressing, allowing 1024 different hosts.

Host address:

8 bits are finally used for host addresses within our subnet. This places a limit of 256 machines that can be on the subnet.

Total address:

The 32 bit address is usually written as 4 integers separated by dots.

Port addresses

A service exists on a host, and is identified by its port. This is a 16 bit number. To send a message to a server, you send it to the port for that service of the host that it is running on. This is not location transparency! Certain of these ports are “well known”.

Sockets:

A socket is a data structure maintained by the system to handle network connections. A socket is created using the call socket. It returns an integer that is like a file descriptor. In fact, under Windows, this handle can be used with Read File and Write File functions.

#include <sys/types.h>

#include <sys/socket.h>

int socket(int family, int type, int protocol);

Here “family” will be AF_INET for IP communications, protocol will be zero, and type will depend on whether TCP or UDP is used. Two processes wishing to communicate over a network create a socket each. These are similar to two ends of a pipe – but the actual pipe does not yet exist.

6.8 JFREE CHART:

JFreeChart is a free 100% Java chart library that makes it easy for developers to display professional quality charts in their applications. JFreeChart’s extensive feature set includes:

A consistent and well-documented API, supporting a wide range of chart types;

A flexible design that is easy to extend, and targets both server-side and client-side applications;

Support for many output types, including Swing components, image files (including PNG and JPEG), and vector graphics file formats (including PDF, EPS and SVG);

JFreeChart is “open source” or, more specifically, free software. It is distributed under the terms of the GNU Lesser General Public Licence (LGPL), which permits use in proprietary applications.

6.8.1. Map Visualizations:

Charts showing values that relate to geographical areas. Some examples include: (a) population density in each state of the United States, (b) income per capita for each country in Europe, (c) life expectancy in each country of the world. The tasks in this project include: Sourcing freely redistributable vector outlines for the countries of the world, states/provinces in particular countries (USA in particular, but also other areas);

Creating an appropriate dataset interface (plus default implementation), a rendered, and integrating this with the existing XYPlot class in JFreeChart; Testing, documenting, testing some more, documenting some more.

6.8.2. Time Series Chart Interactivity

Implement a new (to JFreeChart) feature for interactive time series charts — to display a separate control that shows a small version of ALL the time series data, with a sliding “view” rectangle that allows you to select the subset of the time series data to display in the main chart.

6.8.3. Dashboards

There is currently a lot of interest in dashboard displays. Create a flexible dashboard mechanism that supports a subset of JFreeChart chart types (dials, pies, thermometers, bars, and lines/time series) that can be delivered easily via both Java Web Start and an applet.

6.8.4. Property Editors

The property editor mechanism in JFreeChart only handles a small subset of the properties that can be set for charts. Extend (or reimplement) this mechanism to provide greater end-user control over the appearance of the charts.

CHAPTER 7

APPENDIX

7.1 SAMPLE SOURCE CODE

7.2 SAMPLE OUTPUT

CHAPTER 8

8.1 CONCLUSION

We have proposed Web-based TSA to analyze the traffic problems in a humanizer way. To the best of our knowledge, this is the first attempt to apply sentiment analysis on the area of traffic. The study of TSA will provide us a new perspective when facing with traffic problems.

Our work can be concluded as the following five folds: 1) designing the application architecture of TSA; 2) constructing the related bases for the TSA system; 3) comparing the advantages and disadvantages of both rule- and learning-based approaches based on the characters of web data; 4) proposing an algorithm for the sentiment polarity calculation based on the rule-based approach; and 5) taking consideration of the modifying relationships of sentence patterns and locations in the sentiment polarity calculations.

The task to implement the TSA system into existing ITSs is also critically important, and it does need further research. We suggested that take the policy evaluation part to support decision making of managers and view the evaluation results related to specific location as sensor information. The keynote of implementation is jointly accommodating the traveler’s best interest and reasonable workload. Since TSA is still in its infancy, we anticipate that more techniques will be developed for the joint performance of ITS with the TSA system in the future.

Video Dissemination over Hybrid Cellular and Ad Hoc Networks

22/10/201902/07/2019 by admin

We study the problem of disseminating videos to mobile users by using a hybrid cellular and ad hoc network. In particular, we formulate the problem of optimally choosing the mobile devices that will serve as gateways from the cellular to the ad hoc network, the ad hoc routes from the gateways to individual devices, and the layers to deliver on these ad hoc routes.

We develop a Mixed Integer Linear Program (MILP)-based algorithm, called POPT, to solve this optimization problem. Pocket delivers the highest possible video quality and optimization problem that determines:

1) The mobile devices that will serve as gateways and relay video data from the cellular network to the ad hoc network,

2) The multihop ad hoc routes for disseminating video data

3) The subsets of video data each mobile device relays to the next hops under capacity constraints. We formulate the optimization problem into a Mixed Integer Linear Program (MILP), and propose an MILP-based algorithm, called POPT, to optimally solve the problem.

We recommend the THS algorithm for video streaming over hybrid cellular and ad hoc networks. Last, we also build a real video dissemination system among multiple Android smart phones over a live cellular network. Via actual experiments, we demonstrate the practicality and efficiency of the proposed THS algorithm.

We call it Tree-Based Heuristic Scheduling (THS) algorithm, and it works as follows: We first sort all the transmission units in the W-segment scheduling window in descending order of importance, by layer, segment, and video. We then go through these WL units, and sequentially schedule the transmissions to all mobile devices.

1.2 INTRODUCTION

Mobile devices, such as smart phones and tablets, are getting increasingly popular, and continue to generate record-high amount of mobile data traffic. For example, a Cisco report indicates that mobile data traffic will increase 39 times by 2015. Sixty six percent of the increase is due to video traffic. Unfortunately, existing cellular networks were designed for unicast voice services, and do not natively support multicast and broadcast. Therefore, cellular networks are not suitable for large-scale video dissemination. This was validated by a measurement study, which shows that each HSDPA cell can only support up to six mobile video users at 256 kbps. Thus, disseminating videos to many mobile users over cellular networks could lead to network congestion and degraded user experience.

This network capacity issue may be partially addressed by deploying more cellular base stations, installing dedicated broadcast networks (such as Digital Video Broadcast- Handheld, DVB-H), or upgrading the cellular base stations to support Multimedia Broadcast Multicast Service (MBMS). However, these approaches all result in additional costs for new network infrastructure, and might not be fully compatible with existing mobile devices. Hence, a better way to disseminate videos to many mobile users is critical to the profitability of cellular service providers.

We study video dissemination in hybrid cellular and ad hoc networks in the underlying network, consisting of one or several base stations and multiple mobile devices equipped with heterogeneous network interfaces. Mobile devices not only connect to the base station over the cellular network, but also form an ad hoc network using short-range wireless protocols such as WiFi and Bluetooth. Mobile devices relay video traffic among each other using ad hoc links, leveraging such a free spectrum to alleviate bandwidth bottlenecks and cut down the expense of cellular service providers. Throughout the paper, we denote mobile devices that directly receive video data over the cellular network and relay the receiving data to other mobile devices over the ad hoc network as gateways.

1.3 SCOPE OF THE PROJECT

3G, and 4G cellular networks, and examples of ad hoc networks are WiFi ad hoc and Bluetooth networks. Mobile devices can always receive video data from the base station via cellular links. Distributing videos in a hybrid network is challenging because: Wireless networks are dynamic in terms of connectivity, latency, and capacity and video data require high throughput and low latency. To cope with these challenges, we employ layered video coding, such as H.264/MPEG4.

1.4 LITRATURE SURVEY

RATE CONTROL AND STREAM ADAPTATION FOR SCALABLE VIDEO STREAMING OVER MULTIPLE ACCESS NETWORKS

Author: C. Hsu, N. Freris, J. Singh, and X. Zhu

Publish:” Proc. Int’l Packet Video Workshop (PV ’10), pp. 1-8, Dec.2010.

In a multihomed video streaming system, a video sequence is simultaneously transmitted over multiple access networks to a client. In this paper, we formulate the rate control and a stream adaptation problem into a unified optimization problem, which determines the sending rates of individual networks, selects which video packets to transmit, and assigns each packet to an access network. We propose two heuristic algorithms with a trade-off between optimality and computational complexity. One of the proposed algorithms runs faster, while the other one results in better video quality. We propose a hybrid algorithm that demonstrates a good balance between optimality and computational complexity. We conduct extensive packet-level simulations to evaluate our algorithms using real network conditions and actual scalable video streams. We compare our algorithms against the rate control algorithms defined in the Datagram Congestion Control Protocol (DCCP) standard. The simulation results show that our algorithms significantly outperform current systems while being TCP-friendly. Our algorithms achieve at least 10 dB quality improvements over DCCP and result in up to 83% packet delivery delay reduction.

CHAPTER 2

2.0 SYSTEM ANALYSIS

2.1 EXISTING SYSTEM:

Linear Program (LP)-based algorithm called MTS, for lower time complexity generic ad hoc protocols do not work well in hybrid cellular and WiFi ad hoc networks, and may lead to:

1) degraded overall throughput, 2) unfair resource allocation, and 3) low resilience to mobility. They propose two approaches to improve the efficiency of ad hoc protocols. First, the base station can run optimization algorithms for the WiFi ad hoc network, for example, to build optimized routes. Second, mobile devices connected to other access networks can offload traffic from the cellular network to those access networks, so as to avoid network congestion around the base station.

2.1.1 DISADVANTAGES:

Existing algorithms achieve at least 10 dB quality improvements and result in up to 80% packet delivery delay reduction.

2.2 PROPOSED SYSTEM:

We propose a hybrid network, in which each multicast group is either in the cellular in the ad hoc mode. Initially, all multicast groups are in ad hoc mode, and when the bandwidth requirement of a group exceeds the ad hoc network capacity, the base station picks up that group and switches it into the cellular mode.

In the ad hoc network, a flooding routing protocol is used to discover neighbors and a heuristic is employed to forward video data. Our work differs from in several aspects: 1) we propose a unified optimization problem that jointly finds the optimal gateway mobile devices, ad hoc routes, and video adaptation, 2) we consider existing cellular base stations that may not natively support multicast, and 3) we employ Variable-Bit-Rate (VBR) streams.

More specifically, we empirically measure the mapping between the node location and link capacity several times, and use the resulting values for capacity estimation. We adopt the video traces of H.264/MPEG4 layered videos from an online video library. The mean bit rate and average video quality for each layer of the considered videos are given in Table 2. In this paper, we report sample simulation results of distributing Crew. However, the proposed formulation and solutions are general and also work for the scenarios where mobile devices watch different videos.

2.2.1 ADVANTAGES:

1. The links into mobile devices on breadth-first trees of transmission units with higher quality improvement values are given higher priorities.

2. The links with higher ad hoc link capacities are given higher priorities.

3. The links from mobile devices with higher cellular link capacities are given higher priorities.

2.3 HARDWARE & SOFTWARE REQUIREMENTS:

2.3.1 HARDWARE REQUIREMENT:

v Processor – Pentium –IV

Speed – 1.1 GHz
- RAM – 256 MB (min)
- Hard Disk – 20 GB
- Floppy Drive – 1.44 MB
- Key Board – Standard Windows Keyboard
- Mouse – Two or Three Button Mouse
- Monitor – SVGA

2.3.2 SOFTWARE REQUIREMENTS:

Operating System : Windows XP
Front End : JAVA JDK 1.7
Tool : Eclipse
Document : MS-Office 2007

CHAPTER 3

3.0 SYSTEM DESIGN:

Data Flow Diagram / Use Case Diagram / Flow Diagram:

The DFD is also called as bubble chart. It is a simple graphical formalism that can be used to represent a system in terms of the input data to the system, various processing carried out on these data, and the output data is generated by the system

The data flow diagram (DFD) is one of the most important modeling tools. It is used to model the system components. These components are the system process, the data used by the process, an external entity that interacts with the system and the information flows in the system.

DFD shows how the information moves through the system and how it is modified by a series of transformations. It is a graphical technique that depicts information flow and the transformations that are applied as data moves from input to output.

DFD is also known as bubble chart. A DFD may be used to represent a system at any level of abstraction. DFD may be partitioned into levels that represent increasing information flow and functional detail.

NOTATION:

SOURCE OR DESTINATION OF DATA:

External sources or destinations, which may be people or organizations or other entities

DATA SOURCE:

Here the data referenced by a process is stored and retrieved.

PROCESS:

People, procedures or devices that produce data. The physical component is not identified.

DATA FLOW:

Data moves in a specific direction from an origin to a destination. The data flow is a “packet” of data.

MODELING RULES:

There are several common modeling rules when creating DFDs:

All processes must have at least one data flow in and one data flow out.
All processes should modify the incoming data, producing new forms of outgoing data.
Each data store must be involved with at least one data flow.
Each external entity must be involved with at least one data flow.
A data flow must be attached to at least one process.

3.1 BLOCK DIAGRAM:

ARCHITECTURE DIAGRAM:

3.2 DATAFLOW DIAGRAM:

UML DIAGRAMS:

3.2 USE CASE DIAGRAM:

3.3 CLASS DIAGRAM:

3.4 SEQUENCE DIAGRAM:

3.5 ACTIVITY DIAGRAM:

CHAPTER 4

4.0 IMPLEMENTATION:

UNICAST DATA TRANSFER:

We design a hybrid network that uses a WiFi ad hoc network to route cellular data via other mobile devices with higher cellular data rates. Two neighbor discovery and routing protocols, proactive and on-demand, are proposed. With the former protocol, all devices proactively maintain the states of their immediate neighbors. When a device wants to discover a route to the base station, it issues a route discovery message to a neighbor with the highest cellular data rate. The message is further relayed by the neighbor to its highest rate neighbor until there is no neighbor with higher rate than the relayer or the hop count limit is reached. The final relayer is the one that receives data from the cellular network and propagates data to the original requester. With the on-demand protocol, devices do not maintain their neighbors’ states. A requester discovers a route to the base station by flooding a route discovery message to all its neighbors within a given range.

Higher data rates than that of the previous hops forward the message to the base station, which eventually selects the best path to the requester. Simulation results show that the on-demand protocol typically incurs higher traffic overhead on the cellular network, while the proactive protocol consumes more energy. Through simulations show that generic ad hoc protocols do not work well in hybrid cellular and WiFi ad hoc networks, and may lead to: 1) degraded overall throughput, 2) unfair resource allocation, and 3) low resilience to mobility. They propose two approaches to improve the efficiency of ad hoc protocols. First, the base station can run optimization algorithms for the WiFi ad hoc network, for example, to build optimized routes. Second, mobile devices connected to other access networks can offload traffic from the cellular network to those access networks, so as to avoid network congestion around the base station.

MULTICAST DATA TRANSFER:

Evaluate a hybrid network in which a cellular base station reduces its transmission range to achieve a higher data rate for mobile devices inside its range. Some mobile devices act as gateways and relay data to mobile devices outside the range via a multihop ad hoc network. The analysis and simulation results indicate that up to 70 percent downlink capacity improvement over pure cellular networks is possible. We propose a hybrid network, in which each multicast group is either in the cellular mode or in the ad hoc mode. Initially, all multicast groups are in ad hoc mode, and when the bandwidth requirement of a group exceeds the ad hoc network capacity, the base station picks up that group and switches it into the cellular mode. Park and Kasera consider the gateway node discovery problem, and model the ad hoc interference as a graph coloring problem. Solving this problem allows them to approximate the number of other mobile devices in the transmission range of a specific mobile device in the ad hoc routing problem for multicast services, and also abstract ad hoc interference as a graph. They formulate a problem of finding the relay forest to maximize the overall data rate, and they propose an approximation algorithm.

4.1 ALGORITHM:

A Tree-Based Heuristic Algorithm: THS Both POPT and MTS algorithms employ optimization problem solvers. Although commercial and open-source solvers are available, these solvers might lead to long running time in the worst-case scenarios. Hence, we next propose a greedy scheduling algorithm that does not rely on any solvers. We call it Tree-Based Heuristic Scheduling (THS) algorithm, and it works as follows: We first sort all the transmission units in the W-segment scheduling window in descending order of importance, by layer, segment, and video. We then go through these WL units, and sequentially schedule the transmissions to all mobile devices.

4.2 MODULES:

SERVER CLIENT MODULE:

RESOURCE ALLOCATION:

VIDEO STREAMING:

QUALITY OPTIMIZATION:

4.3 MODULE DESCRIPTION:

SERVER CLIENT MODULE:

Client-server computing or networking is a distributed application architecture that partitions tasks or workloads between service providers (servers) and service requesters, called clients. Often clients and servers operate over a computer network on separate hardware. A server machine is a high-performance host that is running one or more server programs which share its resources with clients. A client also shares any of its resources; Clients therefore initiate communication sessions with servers which await (listen to) incoming requests.

WIMAX RELAY NETWORKS:

WiMAX bandwidth allocation schemes in employ multiple loops to examine the performance of the different combinations of recipients, which results in extremely high computational complexity. The bandwidth allocation scheme proposed in this study applies greedy methods to achieve low computational complexity while incorporating the table-consulting mechanisms to avoid redundant bandwidth allocation scheme can efficiently allocate bandwidth while maintaining low computational complexity. WiMAX provide diverse data rates, H.264/SVC allow a video stream to be split into one base layer and multiple enhancement layers. This study assumes that a video can be split into six layers (one base layer and five enhancement layers) corresponding to the six video quality levels a user with the requirements of 64kbit/s 128 kbit/s can be satisfied by receiving the base layer and one enhancement layer.

RESOURCE ALLOCATION:

Our resource allocation model for two-hop WiMAX relay networks consists of one BS, M RSs, and N SSs. For consistency, the BS is regarded as the 0th RS and is denoted by RS0 in the following discussion, while the RSs are denoted by RS1 to RSM.An SS can associate either with the BS or with one of the RSs, and the number of SSs associated with RSm is denoted by Nm. The notation SSm;n represents the nth SS associated with RSm.

CQm represents the channel quality of the link between the BS and RSm while CQm;n represents the channel quality between RSm and SSm;n. Assume that the video streams for the links with lower channel quality should be transmitted by the modulation schemes with higher reliability.

VIDEO STREAMING:

Scalable video broadcast/multicast solutions efficiently integrates scalable video coding, 3G broadcast and ad-hoc forwarding to balance the system-wide and video quality of all viewers at 3G cell. In our solution, video is downloading into multiple layers. The base station broadcasts different layers at different rates to cover viewers at different ranges. All viewers are guaranteed to receive the base layer, and viewers closer to the base station can receive more enhancement layers. Using WiMAX Relay Networks connections, viewers far away from the base station can obtain from their neighbors closer to the base station the enhancement layers that they cannot receive directly from the base station. Our solution strikes a good balance between the average and worst-case performance for all viewers in the cell. We design multi-hop relay routing schemes to exploit the broadcast nature of ad-hoc transmissions and eliminate redundant video relays from helpers to their receivers.

QUALITY OPTIMIZATION:

Our channel qualities of these links, BSs and RSs can dynamically adapt the downlink modulation and coding schemes (MCSs) for data transmission. When RSs are deployed at appropriate locations between the BSs and SSs, the end-to-end channel qualities can be improved and the BSs and RSs can adopt high data-rate MCSs. Based on this improvement in data rate, IEEE 802.16j systems can offer higher throughput and serve more users than IEEE 802.16e systems. Based on the performance enhancements above, IEEE 802.16j has the potential to provide real-time video multicast services such as mobile IPTV, live video streaming (e.g., athletic events), and online gaming).

However, the BSs should allocate bandwidth efficiently to support such bandwidth-hungry services while guaranteeing the quality of user experience (QoE). The bandwidth allocation problems in IEEE 802.16j networks are more challenging than those in IEEE 802.16e networks because the BSs allocate bandwidth not only to the SSs, but also to the RSs. Multicasting also complicates the bandwidth allocation problems of these factors, designing an efficient bandwidth allocation scheme for video multicast services.

We have presented various bandwidth allocation approaches for video services in IEEE 802.16e networks (i.e., single-hop WiMAX systems). The approaches in and allocate bandwidth by exploiting the common technology of scalable video coding (SVC) specified in the H.264/SVC standard. The H.264/SVC standard is extended from H.264/AVC, and can further split a video stream into a base layer for providing the basic video quality and multiple enhancement layers for providing better video quality layer by-layer.

4.4 EXPRIMENTAL RESULTS

PERFORMANCE IMPROVEMENT:

We investigate the performance improvement achieved by the hybrid network compared to the cellular-only network with varied number of mobile devices U. Fig. 6a shows with 95 percent confidence intervals that, for a PSNR requirement of 30 dB, the Current* scheduler can only support 10 mobile devices. POPT, MTS, and THS algorithms all achieve that quality with any investigated number of mobile devices. Note that these schedulers provide an advantage over Current*—mobile devices receive almost equally—good PSNR. That is, the longest range of 95 percent confidential interval achieved by POPT, MTS, and THS is merely 0.30 dB, while Current* suffers from a much larger range of up to 3.78 dB.

We observe that two algorithms, MTS and THS, achieve similar PSNR, at most 2 dB lower than POPT. Fig. 6b indicates that MTS is more efficient than POPT, but MTS’ running time still increases prohibitively with the increase of device density more device network, MTS takes more than half an hour to generate a schedule. In contrast, the THS algorithm always terminates in very short time under any number of devices. This shows that the THS algorithm achieves a good tradeoff between complexity and solution quality. Because MTS and THS achieve similar PSNR, but THS runs faster than MTS, we do not consider MTS in the remaining comparisons.

CHAPTER 4

5.0 SYSTEM STUDY:

5.1 FEASIBILITY STUDY:

Three key considerations involved in the feasibility analysis are

ECONOMICAL FEASIBILITY
TECHNICAL FEASIBILITY
SOCIAL FEASIBILITY

5.1.1 ECONOMICAL FEASIBILITY:

5.1.2 TECHNICAL FEASIBILITY:

5.1.3 SOCIAL FEASIBILITY:

5.2 SYSTEM TESTING:

Testing is a process of checking whether the developed system is working according to the original objectives and requirements. It is a set of activities that can be planned in advance and conducted systematically. Testing is vital to the success of the system. System testing makes a logical assumption that if all the parts of the system are correct, the global will be successfully achieved. In adequate testing if not testing leads to errors that may not appear even many months. This creates two problems, the time lag between the cause and the appearance of the problem and the effect of the system errors on the files and records within the system. A small system error can conceivably explode into a much larger Problem. Effective testing early in the purpose translates directly into long term cost savings from a reduced number of errors. Another reason for system testing is its utility, as a user-oriented vehicle before implementation. The best programs are worthless if it produces the correct outputs.

5.2.1 UNIT TESTING:

UNIT TESTING:

Description	Expected result
Test for application window properties.	All the properties of the windows are to be properly aligned and displayed.
Test for mouse operations.	All the mouse operations like click, drag, etc. must perform the necessary operations without any exceptions.

5.1.3 FUNCTIONAL TESTING:

FUNCTIONAL TESTING:

Description	Expected result
Test for all modules.	All peers should communicate in the group.
Test for various peer in a distributed network framework as it display all users available in the group.	The result after execution should give the accurate result.

5.1. 4 NON-FUNCTIONAL TESTING:

Load testing
Performance testing
Usability testing
Reliability testing
Security testing

5.1.5 LOAD TESTING:

Load Testing

Description	Expected result
It is necessary to ascertain that the application behaves correctly under loads when ‘Server busy’ response is received.	Should designate another active node as a Server.

5.1.5 PERFORMANCE TESTING:

PERFORMANCE TESTING:

Description	Expected result
This is required to assure that an application perforce adequately, having the capability to handle many peers, delivering its results in expected time and using an acceptable level of resource and it is an aspect of operational management.	Should handle large input values, and produce accurate result in a expected time.

5.1.6 RELIABILITY TESTING:

RELIABILITY TESTING:

Description	Expected result
This is to check that the server is rugged and reliable and can handle the failure of any of the components involved in provide the application.	In case of failure of the server an alternate server should take over the job.

5.1.7 SECURITY TESTING:

SECURITY TESTING:

Description	Expected result
Checking that the user identification is authenticated.	In case failure it should not be connected in the framework.
Check whether group keys in a tree are shared by all peers.	The peers should know group key in the same group.

5.1.7 WHITE BOX TESTING:

5.1.8 WHITE BOX TESTING:

Description	Expected result
Exercise all logical decisions on their true and false sides.	All the logical decisions must be valid.
Execute all loops at their boundaries and within their operational bounds.	All the loops must be finite.
Exercise internal data structures to ensure their validity.	All the data structures must be valid.

5.1.9 BLACK BOX TESTING:

5.1.10 BLACK BOX TESTING:

Description	Expected result
To check for incorrect or missing functions.	All the functions must be valid.
To check for interface errors.	The entire interface must function normally.
To check for errors in a data structures or external data base access.	The database updation and retrieval must be done.
To check for initialization and termination errors.	All the functions and data structures must be initialized properly and terminated normally.

All the above system testing strategies are carried out in as the development, documentation and institutionalization of the proposed goals and related policies is essential.

CHAPTER 7

7.0 SOFTWARE DESCRIPTION:

7.1 JAVA TECHNOLOGY:

Java technology is both a programming language and a platform.

The Java Programming Language

The Java programming language is a high-level language that can be characterized by all of the following buzzwords:

Simple
- Architecture neutral
- Object oriented
- Portable
- Distributed
- High performance
- Interpreted
- Multithreaded
- Robust
- Dynamic
- Secure

7.2 THE JAVA PLATFORM:

The Java platform has two components:

The Java Virtual Machine (Java VM)
The Java Application Programming Interface (Java API)

You’ve already been introduced to the Java VM. It’s the base for the Java platform and is ported onto various hardware-based platforms.

The following figure depicts a program that’s running on the Java platform. As the figure shows, the Java API and the virtual machine insulate the program from the hardware.

7.3 WHAT CAN JAVA TECHNOLOGY DO?

The essentials: Objects, strings, threads, numbers, input and output, data structures, system properties, date and time, and so on.
Applets: The set of conventions used by applets.
Networking: URLs, TCP (Transmission Control Protocol), UDP (User Data gram Protocol) sockets, and IP (Internet Protocol) addresses.
Internationalization: Help for writing programs that can be localized for users worldwide. Programs can automatically adapt to specific locales and be displayed in the appropriate language.
Security: Both low level and high level, including electronic signatures, public and private key management, access control, and certificates.
Software components: Known as JavaBeans^TM, can plug into existing component architectures.
Object serialization: Allows lightweight persistence and communication via Remote Method Invocation (RMI).
Java Database Connectivity (JDBC^TM): Provides uniform access to a wide range of relational databases.

The Java platform also has APIs for 2D and 3D graphics, accessibility, servers, collaboration, telephony, speech, animation, and more. The following figure depicts what is included in the Java 2 SDK.

7.4 HOW WILL JAVA TECHNOLOGY CHANGE MY LIFE?

Get started quickly: Although the Java programming language is a powerful object-oriented language, it’s easy to learn, especially for programmers already familiar with C or C++.
Write less code: Comparisons of program metrics (class counts, method counts, and so on) suggest that a program written in the Java programming language can be four times smaller than the same program in C++.
Write better code: The Java programming language encourages good coding practices, and its garbage collection helps you avoid memory leaks. Its object orientation, its JavaBeans component architecture, and its wide-ranging, easily extendible API let you reuse other people’s tested code and introduce fewer bugs.
Develop programs more quickly: Your development time may be as much as twice as fast versus writing the same program in C++. Why? You write fewer lines of code and it is a simpler programming language than C++.
Avoid platform dependencies with 100% Pure Java: You can keep your program portable by avoiding the use of libraries written in other languages. The 100% Pure Java^TMProduct Certification Program has a repository of historical process manuals, white papers, brochures, and similar materials online.
Write once, run anywhere: Because 100% Pure Java programs are compiled into machine-independent byte codes, they run consistently on any Java platform.
Distribute software more easily: You can upgrade applets easily from a central server. Applets take advantage of the feature of allowing new classes to be loaded “on the fly,” without recompiling the entire program.

7.5 ODBC:

7.6 JDBC:

JDBC was announced in March of 1996. It was released for a 90 day public review that ended June 8, 1996. Because of user input, the final JDBC v1.0 specification was released soon after.

7.7 JDBC Goals:

The goals that were set for JDBC are important. They will give you some insight as to why certain classes and functionalities behave the way they do. The eight design goals for JDBC are as follows:

SQL Level API

SQL Conformance

JDBC must be implemental on top of common database interfaces

Provide a Java interface that is consistent with the rest of the Java system

Because of Java’s acceptance in the user community thus far, the designers feel that they should not stray from the current design of the core Java system.

Keep it simple

Use strong, static typing wherever possible

Strong typing allows for more error checking to be done at compile time; also, less error appear at runtime.

Keep the common cases simple

Finally we decided to precede the implementation using Java Networking.

And for dynamically updating the cache table we go for MS Access database.

Java ha two things: a programming language and a platform.

Java is a high-level programming language that is all of the following

Simple Architecture-neutral

Object-oriented Portable

Distributed High-performance

Interpreted Multithreaded

Robust Dynamic Secure

Compilation happens just once; interpretation occurs each time the program is executed. The figure illustrates how this works.

7.7 NETWORKING TCP/IP STACK:

The TCP/IP stack is shorter than the OSI one:

TCP is a connection-oriented protocol; UDP (User Datagram Protocol) is a connectionless protocol.

IP datagram’s:

UDP:

UDP is also connectionless and unreliable. What it adds to IP is a checksum for the contents of the datagram and port numbers. These are used to give a client/server model – see later.

TCP:

TCP supplies logic to give a reliable connection-oriented protocol above IP. It provides a virtual circuit that two processes can use to communicate.

Internet addresses

In order to use a service, you must be able to find it. The Internet uses an address scheme for machines so that they can be located. The address is a 32 bit integer which gives the IP address.

Network address:

Class A uses 8 bits for the network address with 24 bits left over for other addressing. Class B uses 16 bit network addressing. Class C uses 24 bit network addressing and class D uses all 32.

Subnet address:

Internally, the UNIX network is divided into sub networks. Building 11 is currently on one sub network and uses 10-bit addressing, allowing 1024 different hosts.

Host address:

8 bits are finally used for host addresses within our subnet. This places a limit of 256 machines that can be on the subnet.

Total address:

The 32 bit address is usually written as 4 integers separated by dots.

Port addresses

Sockets:

#include <sys/types.h>

#include <sys/socket.h>

int socket(int family, int type, int protocol);

7.8 JFREE CHART:

JFreeChart is a free 100% Java chart library that makes it easy for developers to display professional quality charts in their applications. JFreeChart’s extensive feature set includes:

A consistent and well-documented API, supporting a wide range of chart types;

A flexible design that is easy to extend, and targets both server-side and client-side applications;

Support for many output types, including Swing components, image files (including PNG and JPEG), and vector graphics file formats (including PDF, EPS and SVG);

JFreeChart is “open source” or, more specifically, free software. It is distributed under the terms of the GNU Lesser General Public Licence (LGPL), which permits use in proprietary applications.

7.8.1. Map Visualizations:

7.8.2. Time Series Chart Interactivity

7.8.3. Dashboards

7.8.4. Property Editors

CHAPTER 7

APPENDIX

7.1 SAMPLE SOURCE CODE

7.2 SAMPLE OUTPUT

CHAPTER 8

8.1 CONCLUSION

We proposed algorithms: 1) an MILP-based algorithm called POPT a greedy algorithm, THS. Via packet-level simulations, we found that neither POPT nor MTS scale to large hybrid networks. This is because they both employ numerical methods to solve optimization problems. Therefore, we recommend the THS algorithm, which terminates in real time even when there are 70+ mobile devices in the hybrid network.

The experimental results from the actual testbed confirm the observations we made in Qualnet simulations: the THS algorithm clearly outperforms the Current* algorithm. Furthermore, the THS algorithm may outperform POPT in real systems, which can be attributed to the long running time of the POPT algorithm. This demonstrates that the THS algorithm is practical and efficient.

The simulation results indicate that the THS algorithm not only runs fast, but also achieves overall video quality close to the optimum: at most 2 dB difference is observed, compared to the POPT algorithm. In contrast, optimum schedules over the cellular network achieve much lower video quality compared to POPT: more than 15 dB difference is observed. We also validated the practicality and efficiency of the THS algorithm using a real testbed in a live cellular network. The experimental results confirm that the THS algorithm result in high video quality. Moreover, the THS algorithm could outperform the POPT algorithm in real systems. This is because although POPT could generate optimal schedules, its high running time may lead to many late segments, which in turn render inferior video quality.

VeDi A Vehicular Crowd-Sourced Video Social Network for VANETs

22/10/201902/07/2019 by admin

CHAPTER 1

1.1 ABSTRACT:

As one of the important members of Internet of Things (IoT), vehicles have seen steep advancement in communication technology. With the advent of Vehicular Ad-Hoc Networks (VANETs), vehicles now can evolve into social interactions to share safety, efficiency, and comfort related messages with other vehicles. In this paper, we study vehicular social network from Social Internet of Things (SIoT) perspective and propose VeDi, a vehicular crowd-sourced video social network for VANETs.When a user shares a video in the VeDi, it can be accessed by other surrounding vehicles. Any social interaction (e.g. view, comment, like) with the video on the roadway are stored in the social network cloud along with the video itself.

In VeDi, every vehicle maintains a list of video related metadata (e.g. blur and shakiness) of available videos which are used to selectively retrieve quality videos by surrounding vehicles. We also present a method to determine representative quality scores for an entire video clip using blur and shakiness values. The prototype implementations and experimental results denote that the proposed system can be a viable option to create video social networks such as youtube, vine, and vimeo by employing vehicular crowd.

1.2 INTRODUCTION

State-of-the-art vehicles are equipped with advanced technologies that enable them to communicate with nearby vehicles by forming vehicular ad-hoc networks (VANETs). There has been growing interest in building a social network of vehicles that can ensure safety of the driver and passengers, and also improve travel efficiency through collaborative application. While main purpose of VANETs is safety and efficiency, there is plenty of room in the allocated bandwidth for comfort applications as well. In this work we study vehicular social network from video sharing perspective. We propose VeDi, a crowd sourced video social network over VANETs. We envision it to be integrated part of future vehicular social network and eventually Internet of Things.

The distribution of multimedia content over vehicular networks is a challenging task for several reasons such as network partitioning due to nodes mobility, and medium contention due to broadcasting nature of the technology. Therefore users cannot browse through all the videos. In VeDi, OBUs automatically calculate metadata description of video through content processing. This metadata description is shared among other OBUs through a Dedicated Short Range Communication (DSRC1) type message called tNote. Furthermore, it is difficult for the users to comprehend quality of complete video from individual frame quality. We experimentally analyse mobile recorded short video clips and find representative blur and shakiness scores for the entire video. The main contributions of the paper are two-fold: an architecture of crowd sourced video social network and quality based metadata description of videos.

1.3 LITRATURE SURVEY

AUTHOR AND PUBLICATION: N. Abbani, M. Jomaa, T. Tarhini, H. Artail, and W. El-Hajj. MANAGING SOCIAL NETWORKS IN VEHICULAR NETWORKS USING TRUST RULES. In Wireless Technology and Applications (ISWTA), 2011 IEEE Symposium on, pages 168–173, Sept 2011.

EXPLANATION:

Drivers and passengers in urban areas may spend large portion of their time waiting in their cars on the road while commuting to and from work, to school, or to the supermarket. Regularities of driving patterns in time and in space motivate the formation of communities of common backgrounds and interests. We propose a model for forming and maintaining Vehicular Social Networks (VSNs) that uses trust principles for admission to social groups, and controlling the interactions among members. This paper describes the details of the design, and proposes a simple but representative probabilistic model for deriving the probability of wrongful admissions and the probability of an agent trusting a malicious node. The experimental results, which were obtained from simulations using the network simulation software ns2, describe metrics related to the dynamics of group formation and time to form groups as well as to detecting malicious members. Our system was able to form social groups with agents of common interests and maintain an accurate trust evaluation of their behavior.

AUTHOR AND PUBLICATION: M. Asefi, J. W. Mark, and X. Shen. AN APPLICATION-CENTRIC INTER-VEHICLE ROUTING PROTOCOL FOR VIDEO STREAMING OVER MULTI-HOP URBAN VANETS. In Communications (ICC), 2011 IEEE International Conference on, pages 1–5. IEEE, 2011.

EXPLANATION:

Service-oriented vehicular networks face challenge to deliver delay-sensitive data such as video packets. Most research on video streaming consider network-centric quality of service (QoS) metrics rather than the user perceived quality. In this paper, we propose an application-centric routing framework for real-time video transmission over urban multi-hop vehicular ad-hoc network (VANET) scenarios. Queueing based mobility model, spatial traffic distribution and probability of connectivity for sparse and dense VANET scenarios are taken into consideration in designing the routing protocol. The numerical results demonstrate the gain achieved by the proposed routing protocol versus geographic greedy forwarding in terms of video frame distortion and streaming start-up delay in several urban communication scenarios for various vehicle entrance rate and traffic densities.

AUTHOR AND PUBLICATION: M. Asefi, J. W. Mark, and X. Shen. A MOBILITY-AWARE AND QUALITYDRIVEN RETRANSMISSION LIMIT ADAPTATION SCHEME FOR VIDEO STREAMING OVER VANETS. Wireless Communications, IEEE Transactions on, 11(5):1817– 1827, 2012.

EXPLANATION:

An adaptive medium access control (MAC) retransmission limit selection scheme is proposed to improve the performance of IEEE 802.11p standard MAC protocol for video streaming applications over vehicular ad-hoc networks (VANETs). A multi-objective optimization framework, which jointly minimizes the probability of playback freezes and start-up delay of the streamed video at the destination vehicle by tuning the MAC retransmission limit with respect to channel statistics as well as packet transmission rate, is applied at road side unit (RSU). Periodic channel state estimation is performed at the RSU using the information derived from the received signal strength (RSS) and Doppler shift effect. Estimates of access probability between the RSU and the destination vehicle is incorporated in the design of the adaptive MAC scheme. The adaptation parameters are embedded in the user datagram protocol (UDP) packet header. Two-hop transmission is applied in zones in which the destination vehicle is not within the transmission range of any RSU. For multi-hop scenario, we discuss two-hop joint MAC retransmission adaptation and path selection. Compared with the non-adaptive IEEE 802.11p standard MAC, numerical results show that the proposed adaptive MAC protocol exhibits significantly fewer playback freezes while introduces only a slight increase in start-up delay.

AUTHOR AND PUBLICATION: L. Atzori, A. Iera, and G. Morabito. SIOT: GIVING A SOCIAL STRUCTURE TO THE INTERNET OF THINGS. Communications Letters, IEEE, 15(11):1193–1195, 2011.

EXPLANATION:

The actual development of the Internet of Things (IoT) needs major issues related to things’ service discovery and composition to be addressed. This paper proposes a possible approach to solve such issues. We introduce a novel paradigm of “social network of intelligent objects”, namely the Social Internet of Things (SIoT), based on the notion of social relationships among objects. Following the definition of a possible social structure among objects, a preliminary architecture for the implementation of SIoT is presented. Through the SIoT paradigm, the capability of humans and devices to discover, select, and use objects with their services in the IoT is augmented. Besides, a level of trustworthiness is enabled to steer the interaction among the billions of objects which will crowd the future IoT.

CHAPTER 2

2.0 SYSTEM ANALYSIS

2.1 EXISTING SYSTEM:

2.1.1 DISADVANTAGES:

2.2 PROPOSED SYSTEM:

2.2.1 ADVANTAGES:

2.3 HARDWARE & SOFTWARE REQUIREMENTS:

2.3.1 HARDWARE REQUIREMENT:

v Processor – Pentium –IV

Speed – 1.1 GHz
- RAM – 256 MB (min)
- Hard Disk – 20 GB
- Floppy Drive – 1.44 MB
- Key Board – Standard Windows Keyboard
- Mouse – Two or Three Button Mouse
- Monitor – SVGA

2.3.2 SOFTWARE REQUIREMENTS:

JAVA

Operating System : Windows XP or Win7
Front End : JAVA JDK 1.7
Back End : MYSQL Server
Server : Apache Tomact Server
Script : JSP Script
Document : MS-Office 2007

.NET

Operating System : Windows XP or Win7
Front End : Microsoft Visual Studio .NET 2008
Script : C# Script
Back End : MS-SQL Server 2005
Document : MS-Office 2007

CHAPTER 3

3.0 SYSTEM DESIGN:

Data Flow Diagram / Use Case Diagram / Flow Diagram:

The DFD is also called as bubble chart. It is a simple graphical formalism that can be used to represent a system in terms of the input data to the system, various processing carried out on these data, and the output data is generated by the system

The data flow diagram (DFD) is one of the most important modeling tools. It is used to model the system components. These components are the system process, the data used by the process, an external entity that interacts with the system and the information flows in the system.

DFD shows how the information moves through the system and how it is modified by a series of transformations. It is a graphical technique that depicts information flow and the transformations that are applied as data moves from input to output.

DFD is also known as bubble chart. A DFD may be used to represent a system at any level of abstraction. DFD may be partitioned into levels that represent increasing information flow and functional detail.

NOTATION:

SOURCE OR DESTINATION OF DATA:

External sources or destinations, which may be people or organizations or other entities

DATA SOURCE:

Here the data referenced by a process is stored and retrieved.

PROCESS:

People, procedures or devices that produce data’s in the physical component is not identified.

DATA FLOW:

Data moves in a specific direction from an origin to a destination. The data flow is a “packet” of data.

MODELING RULES:

There are several common modeling rules when creating DFDs:

All processes must have at least one data flow in and one data flow out.
All processes should modify the incoming data, producing new forms of outgoing data.
Each data store must be involved with at least one data flow.
Each external entity must be involved with at least one data flow.
A data flow must be attached to at least one process.

SYSTEM DESIGN 🙁 user)

User Case Diagram

Class Diagram

Activity Diagram

Sequence Diagram

CHAPTER 4

4.0 IMPLEMENTATION:

4.1 ALGORITHM

4.2 MODULES:

4.3 MODULE DESCRIPTION:

CHAPTER 5

5.0 SYSTEM STUDY:

5.1 FEASIBILITY STUDY:

Three key considerations involved in the feasibility analysis are

ECONOMICAL FEASIBILITY
TECHNICAL FEASIBILITY
SOCIAL FEASIBILITY

5.1.1 ECONOMICAL FEASIBILITY:

5.1.2 TECHNICAL FEASIBILITY

5.1.3 SOCIAL FEASIBILITY:

5.2 SYSTEM TESTING:

5.2.1 UNIT TESTING:

Description	Expected result
Test for application window properties.	All the properties of the windows are to be properly aligned and displayed.
Test for mouse operations.	All the mouse operations like click, drag, etc. must perform the necessary operations without any exceptions.

5.1.2 FUNCTIONAL TESTING:

Description	Expected result
Test for all modules.	All peers should communicate in the group.
Test for various peer in a distributed network framework as it display all users available in the group.	The result after execution should give the accurate result.

5.1. 3 NON-FUNCTIONAL TESTING:

Load testing
Performance testing
Usability testing
Reliability testing
Security testing

5.1.4 LOAD TESTING:

Description	Expected result
It is necessary to ascertain that the application behaves correctly under loads when ‘Server busy’ response is received.	Should designate another active node as a Server.

5.1.5 PERFORMANCE TESTING:

Description	Expected result
This is required to assure that an application perforce adequately, having the capability to handle many peers, delivering its results in expected time and using an acceptable level of resource and it is an aspect of operational management.	Should handle large input values, and produce accurate result in a expected time.

5.1.6 RELIABILITY TESTING:

Description	Expected result
This is to check that the server is rugged and reliable and can handle the failure of any of the components involved in provide the application.	In case of failure of the server an alternate server should take over the job.

5.1.7 SECURITY TESTING:

Description	Expected result
Checking that the user identification is authenticated.	In case failure it should not be connected in the framework.
Check whether group keys in a tree are shared by all peers.	The peers should know group key in the same group.

5.1.8 WHITE BOX TESTING:

Description	Expected result
Exercise all logical decisions on their true and false sides.	All the logical decisions must be valid.
Execute all loops at their boundaries and within their operational bounds.	All the loops must be finite.
Exercise internal data structures to ensure their validity.	All the data structures must be valid.

5.1.9 BLACK BOX TESTING:

Description	Expected result
To check for incorrect or missing functions.	All the functions must be valid.
To check for interface errors.	The entire interface must function normally.
To check for errors in a data structures or external data base access.	The database updation and retrieval must be done.
To check for initialization and termination errors.	All the functions and data structures must be initialized properly and terminated normally.

All the above system testing strategies are carried out in as the development, documentation and institutionalization of the proposed goals and related policies is essential.

CHAPTER 6

6.0 SOFTWARE DESCRIPTION:

6.1 JAVA TECHNOLOGY:

Java technology is both a programming language and a platform.

The Java Programming Language

The Java programming language is a high-level language that can be characterized by all of the following buzzwords:

Simple
- Architecture neutral
- Object oriented
- Portable
- Distributed
- High performance
- Interpreted
- Multithreaded
- Robust
- Dynamic
- Secure

6.2 THE JAVA PLATFORM:

The Java platform has two components:

The Java Virtual Machine (Java VM)
The Java Application Programming Interface (Java API)

You’ve already been introduced to the Java VM. It’s the base for the Java platform and is ported onto various hardware-based platforms.

The following figure depicts a program that’s running on the Java platform. As the figure shows, the Java API and the virtual machine insulate the program from the hardware.

6.3 WHAT CAN JAVA TECHNOLOGY DO?

The essentials: Objects, strings, threads, numbers, input and output, data structures, system properties, date and time, and so on.
Applets: The set of conventions used by applets.
Networking: URLs, TCP (Transmission Control Protocol), UDP (User Data gram Protocol) sockets, and IP (Internet Protocol) addresses.
Internationalization: Help for writing programs that can be localized for users worldwide. Programs can automatically adapt to specific locales and be displayed in the appropriate language.
Security: Both low level and high level, including electronic signatures, public and private key management, access control, and certificates.
Software components: Known as JavaBeans^TM, can plug into existing component architectures.
Object serialization: Allows lightweight persistence and communication via Remote Method Invocation (RMI).
Java Database Connectivity (JDBC^TM): Provides uniform access to a wide range of relational databases.

The Java platform also has APIs for 2D and 3D graphics, accessibility, servers, collaboration, telephony, speech, animation, and more. The following figure depicts what is included in the Java 2 SDK.

6.4 HOW WILL JAVA TECHNOLOGY CHANGE MY LIFE?

Get started quickly: Although the Java programming language is a powerful object-oriented language, it’s easy to learn, especially for programmers already familiar with C or C++.
Write less code: Comparisons of program metrics (class counts, method counts, and so on) suggest that a program written in the Java programming language can be four times smaller than the same program in C++.
Write better code: The Java programming language encourages good coding practices, and its garbage collection helps you avoid memory leaks. Its object orientation, its JavaBeans component architecture, and its wide-ranging, easily extendible API let you reuse other people’s tested code and introduce fewer bugs.
Develop programs more quickly: Your development time may be as much as twice as fast versus writing the same program in C++. Why? You write fewer lines of code and it is a simpler programming language than C++.
Avoid platform dependencies with 100% Pure Java: You can keep your program portable by avoiding the use of libraries written in other languages. The 100% Pure Java^TMProduct Certification Program has a repository of historical process manuals, white papers, brochures, and similar materials online.
Write once, run anywhere: Because 100% Pure Java programs are compiled into machine-independent byte codes, they run consistently on any Java platform.
Distribute software more easily: You can upgrade applets easily from a central server. Applets take advantage of the feature of allowing new classes to be loaded “on the fly,” without recompiling the entire program.

6.5 ODBC:

6.6 JDBC:

JDBC was announced in March of 1996. It was released for a 90 day public review that ended June 8, 1996. Because of user input, the final JDBC v1.0 specification was released soon after.

6.7 JDBC Goals:

The goals that were set for JDBC are important. They will give you some insight as to why certain classes and functionalities behave the way they do. The eight design goals for JDBC are as follows:

SQL Level API

SQL Conformance

JDBC must be implemental on top of common database interfaces

Provide a Java interface that is consistent with the rest of the Java system

Because of Java’s acceptance in the user community thus far, the designers feel that they should not stray from the current design of the core Java system.

Keep it simple

Use strong, static typing wherever possible

Strong typing allows for more error checking to be done at compile time; also, less error appear at runtime.

Keep the common cases simple

Finally we decided to precede the implementation using Java Networking.

And for dynamically updating the cache table we go for MS Access database.

Java ha two things: a programming language and a platform.

Java is a high-level programming language that is all of the following

Simple Architecture-neutral

Object-oriented Portable

Distributed High-performance

Interpreted Multithreaded

Robust Dynamic Secure

Compilation happens just once; interpretation occurs each time the program is executed. The figure illustrates how this works.

6.7 NETWORKING TCP/IP STACK:

The TCP/IP stack is shorter than the OSI one:

TCP is a connection-oriented protocol; UDP (User Datagram Protocol) is a connectionless protocol.

IP datagram’s:

UDP:

UDP is also connectionless and unreliable. What it adds to IP is a checksum for the contents of the datagram and port numbers. These are used to give a client/server model – see later.

TCP:

TCP supplies logic to give a reliable connection-oriented protocol above IP. It provides a virtual circuit that two processes can use to communicate.

Internet addresses

In order to use a service, you must be able to find it. The Internet uses an address scheme for machines so that they can be located. The address is a 32 bit integer which gives the IP address.

Network address:

Class A uses 8 bits for the network address with 24 bits left over for other addressing. Class B uses 16 bit network addressing. Class C uses 24 bit network addressing and class D uses all 32.

Subnet address:

Internally, the UNIX network is divided into sub networks. Building 11 is currently on one sub network and uses 10-bit addressing, allowing 1024 different hosts.

Host address:

8 bits are finally used for host addresses within our subnet. This places a limit of 256 machines that can be on the subnet.

Total address:

The 32 bit address is usually written as 4 integers separated by dots.

Port addresses

Sockets:

#include <sys/types.h>

#include <sys/socket.h>

int socket(int family, int type, int protocol);

6.8 JFREE CHART:

JFreeChart is a free 100% Java chart library that makes it easy for developers to display professional quality charts in their applications. JFreeChart’s extensive feature set includes:

A consistent and well-documented API, supporting a wide range of chart types;

A flexible design that is easy to extend, and targets both server-side and client-side applications;

Support for many output types, including Swing components, image files (including PNG and JPEG), and vector graphics file formats (including PDF, EPS and SVG);

JFreeChart is “open source” or, more specifically, free software. It is distributed under the terms of the GNU Lesser General Public Licence (LGPL), which permits use in proprietary applications.

6.8.1. Map Visualizations:

6.8.2. Time Series Chart Interactivity

6.8.3. Dashboards

6.8.4. Property Editors

CHAPTER 7

APPENDIX

7.1 SAMPLE SOURCE CODE

7.2 SAMPLE OUTPUT

CHAPTER 8

8.1 CONCLUSION

Sharing video over VANETs is challenging due to dynamic and unpredictable topology, low bandwidth, and fleeting connections. In this paper, we have proposed a framework, VeDi, for vehicular crowd sourced video social network over VANETs. In the proposed work, vehicles share metadata based description of videos that are captured by the occupants of the vehicle and are accessible to surrounding vehicles. The metadata consists of video specifications and derived blur and shakiness measures. These metadata scores help video consumers to select the right video while on the roadway. VeDi reduces the overall bandwidth consumption as users can select most appropriate video without downloading them all. We have provided implementation technique of DSRC type tNote message and encoding size analysis at various system instances. A detail about system architecture implementation approach is also provided with various observations. In our future work, we envision presenting the modeling and simulation results of the proposed system along with scalability measurements and required optimizations.

CHAPTER 9

9.1 REFERENCES

N. Abbani, M. Jomaa, T. Tarhini, H. Artail, and W. El-Hajj. Managing social networks in vehicular networks using trust rules. In Wireless Technology and Applications (ISWTA), 2011 IEEE Symposium on, pages 168–173, Sept 2011.

M. Asefi, J. W. Mark, and X. Shen. An application-centric inter-vehicle routing protocol for video streaming over multi-hop urban vanets. In Communications (ICC), 2011 IEEE International Conference on, pages 1–5. IEEE, 2011.

M. Asefi, J. W. Mark, and X. Shen. A mobility-aware and qualitydriven retransmission limit adaptation scheme for video streaming over vanets. Wireless Communications, IEEE Transactions on, 11(5):1817– 1827, 2012.

L. Atzori, A. Iera, and G. Morabito. Siot: Giving a social structure to the internet of things. Communications Letters, IEEE, 15(11):1193–1195, 2011.

L. Atzori, A. Iera, G. Morabito, and M. Nitti. The social internet of things (siot)–when social networks meet the internet of things: Concept, architecture and network characterization. Computer Networks, 2012.

M. Campanella, H. Weda, and M. Barbieri. Edit while watching: home video editing made easy. In Proceedings of SPIE, volume 6506, 2007.

Y.-C. Chu and N.-F. Huang. Delivering of live video streaming for vehicular communication using peer-to-peer approach. In 2007 Mobile Networking for Vehicular Environments, pages 1–6. IEEE, 2007.

Supporting Privacy Protection in Personalized Web Search

22/10/201902/07/2019 by admin

Sleep Scheduling for Geographic Routing in Duty-Cycled Mobile Sensor Networks

22/10/201902/07/2019 by admin

Security Analysis of Handover Key Management in 4G LTESAE Networks

22/10/201902/07/2019 by admin

Secure De-duplication with Efficient and Reliable Convergent Key Management

22/10/201902/07/2019 by admin

Secure and Efficient Data Transmission for Cluster-Based Wireless Sensor Networks

22/10/201902/07/2019 by admin

SECURE AND EFFICIENT DATA TRANSMISSION FOR CLUSTER-BASED

WIRELESS SENSOR NETWORKS

PROJECT REPORT

Submitted to the Department of Computer Science & Engineering in the FACULTY OF ENGINEERING & TECHNOLOGY

In partial fulfillment of the requirements for the award of the degree

MASTER OF TECHNOLOGY

COMPUTER SCIENCE & ENGINEERING

APRIL 2015

BONAFIDE CERTIFICATE

Certified that this project report titled “SECURE AND EFFICIENT DATA TRANSMISSION FOR CLUSTER-BASED WIRELESS SENSOR NETWORKS SYSTEMS” is the bonafide work of Mr. _____________Who carried out the research under my supervision Certified further, that to the best of my knowledge the work reported herein does not form part of any other project report or dissertation on the basis of which a degree or award was conferred on an earlier occasion on this or any other candidate.

Signature of the Guide Signature of the H.O.D

Name Name

CHAPTER 1

ABSTRACT:

Secure data transmission is a critical issue for wireless sensor networks (WSNs).Clustering is an effective and practical way to enhance the system performance of WSNs. In this paper, we study a secure data transmission for cluster-based WSNs (CWSNs), where the clusters are formed dynamically and periodically. We propose two Secure and Efficient data Transmission (SET) protocols for CWSNs, called SET-IBS and SET-IBOOS, by using the Identity-Based digital Signature (IBS) scheme and the Identity-Based Online/Offline digital Signature (IBOOS) scheme, respectively. In SET-IBS, security relies on the hardness of the Difﬁe-Hellman problem in the pairing domain. SET-IBOOS further reduces the computational overhead for protocol security, which is crucial for WSNs, while its security relies on the hardness of the discrete logarithm problem. We show the feasibility of the SET-IBS and SET-IBOOS protocols with respect to the security requirements and security analysis against various attacks. The calculations and simulations are provided to] illustrate the efficiency of the proposed protocols. The results show that, the proposed protocols have better performance than the existing secure protocols for CWSNs, in terms of security overhead and energy consumption.

1.2 INTRODUCTION

A sensor network (WSN) is a network system comprised of spatially distributed devices using wireless sensor nodes to monitor physical or environmental conditions, such as sound, temperature, and motion. The individual nodes are capable of sensing their environments, processing the information data locally, and sending data to one or more collection points in a WSN. Eﬃcient data transmission is one of the most important issues for WSNs. Meanwhile, many WSNs are deployed in harsh, neglected and often adversarial physical environments for certain applications, such as military domains and sensing tasks with trustless surroundings. Secure and eﬃcient data transmission is thus especially necessary and is demanded in many such practical WSNs.

Cluster-based data transmission in WSNs has been investigated by researchers to achieve the network scalability and management, which maximizes node lifetime and reduce bandwidth consumption by using local collaboration among sensor nodes in a cluster-based WSN (CWSN), every cluster has a leader sensor node, regarded as cluster head (CH). A CH aggregates the data collected by the leaf nodes (non-CH sensor nodes) in its cluster, and sends the aggregation to the base station (BS). The low-energy adaptive clustering hierarchy (LEACH) protocol is a widely known and effective one to reduce and balance the total energy consumption for CWSNs. To prevent quick energy consumption of the set of CHs, LEACH randomly rotates CHs among all sensor nodes in the network, in rounds. LEACH achieves improvements in terms of network lifetime. Following the idea of LEACH, a number of protocols have been presented such as APTEEN and PEACH which use similar concepts of LEACH. In this paper, for convenience, we call this sort of cluster-based protocols as LEACH-like protocols.

Researchers have been widely studying CWSNs in the last decade in the literature. However, the implementation of the cluster-based architecture in the real world is rather complicated. Adding security to LEACH-like protocols is challenging because they dynamically, randomly, and periodically rearrange the network’s clusters and data links. Therefore, providing steady long-lasting node-to-node trust relationships and common key distributions are inadequate for LEACH-like protocols (most existing solutions are provided for distributed WSNs, but not for CWSNs). There are some secure data transmission protocols based on LEACH-like protocols, such as SecLEACH, GS-LEACH, and RLEACH.

Most of them, however, apply the symmetric key management for security, which suffers from a so-called orphan node problem occurs when a node does not share a pairwise key with others in its preloaded key ring. To mitigate the storage cost of symmetric keys, the key ring in a node is not sufficient for it to share pairwise symmetric keys with all of the nodes in a network. In such a case, it cannot participate in any cluster, and therefore, has to elect itself as a CH. Furthermore, the orphan node problem reduces the possibility of a node joining with a CH, when the number of alive nodes owning pairwise keys decreases after a long-term operation of the network.

Since the more CHs elected by them, the more overall energy consumed of the network the orphan node problem increases the overhead of transmission and system energy consumption by raising the number of CHs. Even in the case that a sensor node does share a pairwise key with a distant CH but not a nearby CH, it requires comparatively high energy to transmit data to the distant CH. The feasibility of the asymmetric key management has been shown in WSNs recently, which compensates the shortage from applying the symmetric key management for security. Digital signature is one of the most critical security services offered by cryptography in asymmetric key management systems, where the binding between the public key and the identification of the signer is obtained via a digital certificate. The identity-based digital signature (IBS) scheme, based on the difficulty of factoring integers from identity-based cryptography (IBC), is to derive an entity’s public key from its identity information, for example, from its name or ID number.

Recently, the concept of IBS has been developed as a key management in WSNs for security. Carman first combined the benefits of IBS and key predistribution set into WSNs, and some papers appeared in recent years IBOOS scheme has been proposed to reduce the computation and storage costs of signature processing. A general method for constructing online/offline signature schemes was introduced by Even et al. The IBOOS scheme could be effective for the key management in WSNs. Specifically; the offline phase can be executed on a sensor node or at the BS prior to communication, while the online phase is to be executed during communication. Some IBOOS schemes are designed for WSNs afterwards, such as [20] and [21]. The offline signature in these schemes, however, is precomputed by a third party and lacks reusability, thus they are not suitable for CWSNs.

LITRATURE SURVEY

A SECURE ROUTING PROTOCOL FOR CLUSTER-BASED WIRELESS SENSOR NETWORKS USING ID-BASED DIGITAL SIGNATURE

AUTHOR: H. Lu, J. Li, and H. Kameda,

PUBLISH: Proc. IEEE GLOBECOM, pp. 1-5, 2010.

In this paper, we study the secure routing for cluster-based sensor networks where clusters are formed dynamically and periodically. We point out the deficiency in the secure routing protocols with symmetric key pairing. Along with the investigation of ID-based cryptography for security in WSNs, we propose a new secure routing protocol with ID-based signature scheme for cluster-based WSNs, in which the security relies on the hardness of the Diffie-Hellman problem in the random oracle model. Because of the communication overhead for security, we provide analysis and simulation results in details to illustrate how various parameters act between security and energy efficiency.

AN IDENTITY-BASED SECURITY SYSTEM FOR USER PRIVACY IN VEHICULAR AD HOC NETWORKS

AUTHOR: J. Sun et al., IEEE Trans. Parallel & Distributed Systems,

Vehicular ad hoc network (VANET) can offer various services and benefits to users and thus deserves deployment effort. Attacking and misusing such network could cause destructive consequences. It is therefore necessary to integrate security requirements into the design of VANETs and defend VANET systems against misbehavior, in order to ensure correct and smooth operations of the network. In this paper, we propose a security system for VANETs to achieve privacy desired by vehicles and traceability required by law enforcement authorities, in addition to satisfying fundamental security requirements including authentication, nonrepudiation, message integrity, and confidentiality. Moreover, we propose a privacy-preserving defense technique for network authorities to handle misbehavior in VANET access, considering the challenge that privacy provides avenue for misbehavior. The proposed system employs an identity-based cryptosystem where certificates are not needed for authentication. We show the fulfillment and feasibility of our system with respect to the security goals and efficiency.

A SECURE ROUTING PROTOCOL FOR CLUSTER-BASED WIRELESS SENSOR NETWORKS USING GROUP KEY MANAGEMENT

AUTHOR: K. Zhang, C. Wang, and C. Wang,

PUBLISH: Proc. Fourth Int’l Conf. Wireless Comm., Networking and Mobile Computing (WiCOM), pp. 1-5, 2008.

Wireless sensor networks routing protocols always neglect security problem at the designing step, while plenty of solutions of this problem exist, one of which is using key management. Researchers have proposed many key management schemes, but most of them were designed for flat wireless sensor networks, which is not fit for cluster-based wireless sensor networks (e.g. LEACH). In this paper, we investigate adding security to cluster-based routing protocols for wireless sensor networks which consisted of sensor nodes with severely limited resources, and propose a security solution for LEACH, a protocol in which the clusters are formed dynamically and periodically. Our solution uses improved random pair-wise keys (RPK) scheme, an optimized security scheme that relys on symmetric-key methods; is lightweight and preserves the core of the original LEACH. Simulations show that security of RLEACH has been improved, with less energy consumption and lighter overhead.

CHAPTER 2

2.0 SYSTEM ANALYSIS

2.1 EXISTING SYSTEM:

LEACH-like protocols is challenging because they dynamically, randomly, and periodically rearrange the network’s clusters and data links providing steady long-lasting node-to-node trust relationships and common key distributions are inadequate for LEACH-like protocols (most existing solutions are provided for distributed WSNs, but not for CWSNs). There are some secure data transmission protocols based on LEACH-like protocols, such as SecLEACH, GS-LEACH and RLEACH. Most of them, however, apply the symmetric key management for security, which suffers from a so-called orphan node problem occurs when a node does not share a pairwise key with others in its preloaded key ring. To mitigate the storage cost of symmetric keys, the key ring in a node is not sufficient for it to share pairwise symmetric keys with all of the nodes in a network. In such a case, it cannot participate in any cluster, and therefore, has to elect itself as a CH. Furthermore, the orphan node problem reduces the possibility of a node joining with a CH, when the number of alive nodes owning pairwise keysdecreases after a long-term operation of the network.

2.1.1 DISADVANTAGES:

Low-Energy Adaptive Clustering Hierarchy (or LEACH) was one of the first major improvements on conventional clustering approaches in wireless sensor networks. Conventional approaches algorithms such as MTE (Minimum-Transmission-Energy) or direct-transmission do not lead to even energy dissipation throughout a network. LEACH provides a balancing of energy usage by random rotation of clusterheads. The algorithm is also organized in such a manner that data-fusion can be used to reduce the amount of data transmission in very slowly and security issues.

2.2 PROPOSED SYSTEM:

Recently, the concept of IBS has been developed as a key management in WSNs for security. Carman first combined the benefits of IBS and key pre distribution set into WSNs, and some papers appeared in IBOOS scheme has been proposed to reduce the computation and storage costs of signature processing. A general method for constructing online/offline signature schemes was introduced IBOOS scheme could be effective for the key management in WSNs. Specifically, the offline phase can be executed on a sensor node or at the BS prior to communication, while the online phase is to be executed during communication.

We propose two Secure and Efficient data Transmission protocols for CWSNs, called SET-IBS and SET-IBOOS, by using the IBS scheme and the IBOOS scheme, respectively. The key idea of both SET-IBS and SET-IBOOS is to authenticate the encrypted sensed data, by applying digital signatures to message packets, which are efficient in communication and applying the key management for security. In the proposed protocols, secret keys and pairing parameters are distributed and preloaded in all sensor nodes by the BS initially, which overcomes the key escrow problem described in ID-based cryptosystems.

2.2.1 ADVANTAGES:

Secure communication in SET-IBS relies on the IDbased cryptography, in which, user public keys are their ID information. Thus, users can obtain the corresponding private keys without auxiliary data transmission, which is efficient in communication and saves energy.

SET-IBOOS is proposed to further reduce the computational overhead for security using the IBOOS scheme, in which security relies on the hardness of the discrete logarithmic problem. Both SET-IBS and SET-IBOOS solve the orphan node problem in the secure data transmission with a symmetric key management.

We show the feasibility of the proposed protocols with respect to the security requirements and analysis against three attack models. Moreover, we compare the proposed protocols with the existing secure protocols for efficiency by calculations and simulations, respectively, with respect to both computation and communication.

2.3 HARDWARE & SOFTWARE REQUIREMENTS:

2.3.1 HARDWARE REQUIREMENT:

v Processor – Pentium –IV

Speed – 1.1 GHz
- RAM – 256 MB (min)
- Hard Disk – 20 GB
- Floppy Drive – 1.44 MB
- Key Board – Standard Windows Keyboard
- Mouse – Two or Three Button Mouse
- Monitor – SVGA

2.3.2 SOFTWARE REQUIREMENTS:

Operating System : Windows XP or Win7
Front End : JAVA JDK 1.7
Document : MS-Office 2007

CHAPTER 3

3.0 SYSTEM DESIGN:

ARCHITECTURE DIAGRAM / UML DIAGRAMS / DAT FLOW DIAGRAM:

The DFD is also called as bubble chart. It is a simple graphical formalism that can be used to represent a system in terms of the input data to the system, various processing carried out on these data, and the output data is generated by the system

The data flow diagram (DFD) is one of the most important modeling tools. It is used to model the system components. These components are the system process, the data used by the process, an external entity that interacts with the system and the information flows in the system.

DFD shows how the information moves through the system and how it is modified by a series of transformations. It is a graphical technique that depicts information flow and the transformations that are applied as data moves from input to output.

DFD is also known as bubble chart. A DFD may be used to represent a system at any level of abstraction. DFD may be partitioned into levels that represent increasing information flow and functional detail.

NOTATION:

SOURCE OR DESTINATION OF DATA:

External sources or destinations, which may be people or organizations or other entities

DATA SOURCE:

Here the data referenced by a process is stored and retrieved.

PROCESS:

People, procedures or devices that produce data. The physical component is not identified.

DATA FLOW:

Data moves in a specific direction from an origin to a destination. The data flow is a “packet” of data.

MODELING RULES:

There are several common modeling rules when creating DFDs:

All processes must have at least one data flow in and one data flow out.
All processes should modify the incoming data, producing new forms of outgoing data.
Each data store must be involved with at least one data flow.
Each external entity must be involved with at least one data flow.
A data flow must be attached to at least one process.

3.1 ARCHITECTURE DIAGRAM

3.2 DATAFLOW DIAGRAM

UML DIAGRAMS:

3.2 USE CASE DIAGRAM:

3.3 CLASS DIAGRAM:

3.4 SEQUENCE DIAGRAM

3.5 ACTIVITY DIAGRAM:

CHAPTER 4

4.0 IMPLEMENTATION:

We assume that all sensor nodes and the BS are time synchronized with symmetric radio channels, nodes are distributed randomly, and their energy is constrained. In CWSNs, data sensing, processing, and transmission consume energy of sensor nodes. The cost of data transmission is much more expensive than that of data processing. Thus, the method that the intermediate node (e.g., a CH) aggregates data and sends it to the BS is preferred than the method that each sensor node directly sends data to the BS. A sensor node switches into sleep mode for energy saving when it does not sense or transmit data, depending on the time-division multiple access (TDMA) control used for data transmission. In this paper, the proposed SET-IBS and SET-IBOOS are both designed for the same scenarios of CWSNs above.

An IBS scheme implemented for CWSNs consists of the following operations, specifically, setup at the BS, key extraction and signature signing at the data sending nodes, and verification at the data receiving nodes:

. Setup. The BS (as a trust authority) generates a master key msk and public parameters param for the private key generator (PKG), and gives them to all sensor nodes.

. Extraction. Given an ID string, a sensor node generates a private key sekID associated with the

ID using msk.

. Signature signing. Given a message M, time stamp t and a signing key _, the sending node generates a signature SIG.

. Verification. Given the ID, M, and SIG, the receiving node outputs “accept” if SIG is valid, and outputs “reject” otherwise.

4.1 PROTOCOL AND ALGORITHM

SET-IBOOS PROTOCOL

We present the SET protocol for CWSNs by using IBOOS (SET-IBOOS) in this section. The SET-IBOOS protocol is designed with the same purpose and scenarios for CWSNs with higher efficiency. The proposed SET-IBOOS operates similarly to the previous SET-IBS, which has a protocol initialization prior to the network deployment and operates in rounds during communication. We first introduce the protocol initialization, and then describe the key management of the protocol by using the IBOOS scheme, and the protocol operations afterwards. To reduce the computation and storage costs of signature signing processing in the IBS scheme, we improve SET-IBS by introducing IBOOS for security in SET-IBOOS. The operation of the protocol initialization in SET-IBOOS is similar to that of SET-IBS; however, the operations of key predistribution are revised for IBOOS. The BS does the following operations of key predistribution in the network:

4.2 MODULES:

SERVER CLIENT MODULE:

NETWORK SECURITY:

ATTACK MODELS:

PROTOCOL CHARACTERISTICS:

SECURE DATA TRANSMISSION:

4.3 MODULES DESCRIPTION:

SERVER CLIENT MODULE:

NETWORK SECURITY:

Network-accessible resources may be deployed in a network as surveillance and early-warning tools, as the detection of attackers are not normally accessed for legitimate purposes. Techniques used by the attackers that attempt to compromise these decoy resources are studied during and after an attack to keep an eye on new exploitation techniques. Such analysis may be used to further tighten security of the actual network being protected by the data’s.

Data forwarding can also direct an attacker’s attention away from legitimate servers. A user encourages attackers to spend their time and energy on the decoy server while distracting their attention from the data on the real server. Similar to a server, a user is a network set up with intentional vulnerabilities. Its purpose is also to invite attacks so that the attacker’s methods can be studied and that information can be used to increase network security.

ATTACK MODELS:

In this paper, we group attack models into three categories according to their attacking means as follows, and study how these attacks may be applied to affect the proposed protocols:

. Passive attack on wireless channel: Passive attackers are able to perform eavesdropping at any point of the network, or even the whole communication of the network. Thus, they can undertake traffic analysis or statistical analysis based on the monitored or eavesdropped messages.

. Active attack on wireless channel: Active attackers have greater ability than passive adversaries, which can tamper with the wireless channels. Therefore, the attackers can forge, reply, and modify messages. Especially in WSNs, various types of active attacks can be triggered by attackers, such as bogus and replayed routing information attack, sinkhole and wormhole attack.

. Node compromising attack: Node compromising attackers are the most powerful adversaries against the proposed protocols as we considered. The attackers can physically compromise sensor nodes, by which they can access the secret information stored in the compromised nodes, for example, the security keys. The attackers also can change the inner state and behavior of the compromised sensor node, whose actions may be varied from the premier protocol specifications.

PROTOCOL CHARACTERISTICS:

The protocol characteristics and hierarchical clustering solutions are presented in this section. We first summarize the features of the proposed SET-IBS and SET-IBOOS protocols as follows:

Key management: The key cryptographies used in the protocol to achieve secure data transmission, which consist of symmetric and asymmetric key based security.

Neighborhood authentication: Used for secure access and data transmission to nearby sensor nodes, by authenticating with each other. Here, “limited” means the probability of neighborhood authentication, where only the nodes with the shared pairwise key can authenticate each other.

Storage cost: Represents the requirement of the security keys stored in sensor node’s memory.

Network scalability: Indicates whether a security protocol is able to scale without compromising the security requirements. Here, “comparatively low” means that, compared with SET-IBS and SET-IBOOS, in the secure data transmission with a symmetric key management, the larger network scale increases, the more orphan nodes appear in the network, and vice versa.

Communication overhead: The security overhead in the data packets during communication.

Computational overhead: The energy cost and computation efficiency on the generation and verification of the certificates or signatures for security.

Attack resilience: the types of attacks that security protocol can protect against.

SECURE DATA TRANSMISSION:

In large-scale CWSNs, multihop data transmission is used for transmission between the CHs to the BS, where the direct communication is not possible due to the distance or obstacles between them. The version of the proposed SET-IBS and SET-IBOOS protocols for CWSNs can be extended using multihop routing algorithms, to form secure data transmission protocols for hierarchical clusters.

The solutions to this extension could be achieved by applying the following two routing models:

1. The multihop planar model. A CH node transmits data to the BS by forwarding its data to its neighbor nodes, in turn the data are sent to the BS. We have proposed an energy-efficient routing algorithm for hierarchically clustered WSNs in suitable for the proposed secure data transmission protocols.

2. The cluster-based hierarchical method. The network is broken into clustered layers, and the data packages travel from a lower cluster head to a higher one, in turn to the BS.

3. Both the proposed SET-IBS and SET-IBOOS protocols provide secure data transmission for CWSNs with concrete ID-based settings, which use ID information and digital signature for authentication. Thus, both SET-IBS and SET-IBOOS fully solve the orphan-node problem from using the symmetric key management for CWSNs.

4. The proposed secure data transmission protocols are with concrete ID-based settings, which use ID information and digital signature for verification.

CHAPTER 5

5.0 SYSTEM STUDY:

5.1 FEASIBILITY STUDY:

Three key considerations involved in the feasibility analysis are

ECONOMICAL FEASIBILITY
TECHNICAL FEASIBILITY
SOCIAL FEASIBILITY

5.1.1 ECONOMICAL FEASIBILITY:

5.1.2 TECHNICAL FEASIBILITY:

5.1.3 SOCIAL FEASIBILITY:

5.2 SYSTEM TESTING:

5.2.1 UNIT TESTING:

UNIT TESTING:

Description	Expected result
Test for application window properties.	All the properties of the windows are to be properly aligned and displayed.
Test for mouse operations.	All the mouse operations like click, drag, etc. must perform the necessary operations without any exceptions.

5.1.3 FUNCTIONAL TESTING:

FUNCTIONAL TESTING:

Description	Expected result
Test for all modules.	All peers should communicate in the group.
Test for various peer in a distributed network framework as it display all users available in the group.	The result after execution should give the accurate result.

5.1. 4 NON-FUNCTIONAL TESTING:

Load testing
Performance testing
Usability testing
Reliability testing
Security testing

5.1.5 LOAD TESTING:

Load Testing

Description	Expected result
It is necessary to ascertain that the application behaves correctly under loads when ‘Server busy’ response is received.	Should designate another active node as a Server.

5.1.5 PERFORMANCE TESTING:

PERFORMANCE TESTING:

Description	Expected result
This is required to assure that an application perforce adequately, having the capability to handle many peers, delivering its results in expected time and using an acceptable level of resource and it is an aspect of operational management.	Should handle large input values, and produce accurate result in a expected time.

5.1.6 RELIABILITY TESTING:

RELIABILITY TESTING:

Description	Expected result
This is to check that the server is rugged and reliable and can handle the failure of any of the components involved in provide the application.	In case of failure of the server an alternate server should take over the job.

5.1.7 SECURITY TESTING:

SECURITY TESTING:

Description	Expected result
Checking that the user identification is authenticated.	In case failure it should not be connected in the framework.
Check whether group keys in a tree are shared by all peers.	The peers should know group key in the same group.

5.1.7 WHITE BOX TESTING:

5.1.8 WHITE BOX TESTING:

Description	Expected result
Exercise all logical decisions on their true and false sides.	All the logical decisions must be valid.
Execute all loops at their boundaries and within their operational bounds.	All the loops must be finite.
Exercise internal data structures to ensure their validity.	All the data structures must be valid.

5.1.9 BLACK BOX TESTING:

5.1.10 BLACK BOX TESTING:

Description	Expected result
To check for incorrect or missing functions.	All the functions must be valid.
To check for interface errors.	The entire interface must function normally.
To check for errors in a data structures or external data base access.	The database updation and retrieval must be done.
To check for initialization and termination errors.	All the functions and data structures must be initialized properly and terminated normally.

All the above system testing strategies are carried out in as the development, documentation and institutionalization of the proposed goals and related policies is essential.

CHAPTER 6

6.0 SOFTWARE DESCRIPTION:

6.1 JAVA TECHNOLOGY:

Java technology is both a programming language and a platform.

The Java Programming Language

The Java programming language is a high-level language that can be characterized by all of the following buzzwords:

Simple
- Architecture neutral
- Object oriented
- Portable
- Distributed
- High performance
- Interpreted
- Multithreaded
- Robust
- Dynamic
- Secure

6.2 THE JAVA PLATFORM:

The Java platform has two components:

The Java Virtual Machine (Java VM)
The Java Application Programming Interface (Java API)

You’ve already been introduced to the Java VM. It’s the base for the Java platform and is ported onto various hardware-based platforms.

The following figure depicts a program that’s running on the Java platform. As the figure shows, the Java API and the virtual machine insulate the program from the hardware.

6.3 WHAT CAN JAVA TECHNOLOGY DO?

The essentials: Objects, strings, threads, numbers, input and output, data structures, system properties, date and time, and so on.
Applets: The set of conventions used by applets.
Networking: URLs, TCP (Transmission Control Protocol), UDP (User Data gram Protocol) sockets, and IP (Internet Protocol) addresses.
Internationalization: Help for writing programs that can be localized for users worldwide. Programs can automatically adapt to specific locales and be displayed in the appropriate language.
Security: Both low level and high level, including electronic signatures, public and private key management, access control, and certificates.
Software components: Known as JavaBeans^TM, can plug into existing component architectures.
Object serialization: Allows lightweight persistence and communication via Remote Method Invocation (RMI).
Java Database Connectivity (JDBC^TM): Provides uniform access to a wide range of relational databases.

The Java platform also has APIs for 2D and 3D graphics, accessibility, servers, collaboration, telephony, speech, animation, and more. The following figure depicts what is included in the Java 2 SDK.

6.4 HOW WILL JAVA TECHNOLOGY CHANGE MY LIFE?

Get started quickly: Although the Java programming language is a powerful object-oriented language, it’s easy to learn, especially for programmers already familiar with C or C++.
Write less code: Comparisons of program metrics (class counts, method counts, and so on) suggest that a program written in the Java programming language can be four times smaller than the same program in C++.
Write better code: The Java programming language encourages good coding practices, and its garbage collection helps you avoid memory leaks. Its object orientation, its JavaBeans component architecture, and its wide-ranging, easily extendible API let you reuse other people’s tested code and introduce fewer bugs.
Develop programs more quickly: Your development time may be as much as twice as fast versus writing the same program in C++. Why? You write fewer lines of code and it is a simpler programming language than C++.
Avoid platform dependencies with 100% Pure Java: You can keep your program portable by avoiding the use of libraries written in other languages. The 100% Pure Java^TMProduct Certification Program has a repository of historical process manuals, white papers, brochures, and similar materials online.
Write once, run anywhere: Because 100% Pure Java programs are compiled into machine-independent byte codes, they run consistently on any Java platform.
Distribute software more easily: You can upgrade applets easily from a central server. Applets take advantage of the feature of allowing new classes to be loaded “on the fly,” without recompiling the entire program.

6.5 ODBC:

Microsoft Open Database Connectivity (ODBC) is a standard programming interface for application developers and database systems providers. Before ODBC became a de facto standard for Windows programs to interface with database systems, programmers had to use proprietary languages for each database they wanted to connect to. Now, ODBC has made the choice of the database system almost irrelevant from a coding perspective, which is as it should be. Application developers have much more important things to worry about than the syntax that is needed to port their program from one database to another when business needs suddenly change.

6.6 JDBC:

JDBC was announced in March of 1996. It was released for a 90 day public review that ended June 8, 1996. Because of user input, the final JDBC v1.0 specification was released soon after.

6.7 JDBC Goals:

The goals that were set for JDBC are important. They will give you some insight as to why certain classes and functionalities behave the way they do. The eight design goals for JDBC are as follows:

SQL Level API

SQL Conformance

JDBC must be implemental on top of common database interfaces

Provide a Java interface that is consistent with the rest of the Java system

Because of Java’s acceptance in the user community thus far, the designers feel that they should not stray from the current design of the core Java system.

Keep it simple

Use strong, static typing wherever possible

Strong typing allows for more error checking to be done at compile time; also, less error appear at runtime.

Keep the common cases simple

Finally we decided to precede the implementation using Java Networking.

And for dynamically updating the cache table we go for MS Access database.

Java ha two things: a programming language and a platform.

Java is a high-level programming language that is all of the following

Simple Architecture-neutral

Object-oriented Portable

Distributed High-performance

Interpreted Multithreaded

Robust Dynamic Secure

Compilation happens just once; interpretation occurs each time the program is executed. The figure illustrates how this works.

7.7 NETWORKING TCP/IP STACK:

The TCP/IP stack is shorter than the OSI one:

TCP is a connection-oriented protocol; UDP (User Datagram Protocol) is a connectionless protocol.

IP datagram’s:

UDP:

UDP is also connectionless and unreliable. What it adds to IP is a checksum for the contents of the datagram and port numbers. These are used to give a client/server model – see later.

TCP:

TCP supplies logic to give a reliable connection-oriented protocol above IP. It provides a virtual circuit that two processes can use to communicate.

Internet addresses

In order to use a service, you must be able to find it. The Internet uses an address scheme for machines so that they can be located. The address is a 32 bit integer which gives the IP address.

Network address:

Class A uses 8 bits for the network address with 24 bits left over for other addressing. Class B uses 16 bit network addressing. Class C uses 24 bit network addressing and class D uses all 32.

Subnet address:

Internally, the UNIX network is divided into sub networks. Building 11 is currently on one sub network and uses 10-bit addressing, allowing 1024 different hosts.

Host address:

8 bits are finally used for host addresses within our subnet. This places a limit of 256 machines that can be on the subnet.

Total address:

The 32 bit address is usually written as 4 integers separated by dots.

Port addresses

Sockets:

#include <sys/types.h>

#include <sys/socket.h>

int socket(int family, int type, int protocol);

6.8 JFREE CHART:

JFreeChart is a free 100% Java chart library that makes it easy for developers to display professional quality charts in their applications. JFreeChart’s extensive feature set includes:

A consistent and well-documented API, supporting a wide range of chart types;

A flexible design that is easy to extend, and targets both server-side and client-side applications;

Support for many output types, including Swing components, image files (including PNG and JPEG), and vector graphics file formats (including PDF, EPS and SVG);

JFreeChart is “open source” or, more specifically, free software. It is distributed under the terms of the GNU Lesser General Public Licence (LGPL), which permits use in proprietary applications.

6.8.1. Map Visualizations:

6.8.2. Time Series Chart Interactivity

6.8.3. Dashboards

6.8.4. Property Editors

CHAPTER 7

APPENDIX

7.1 SAMPLE SOURCE CODE

7.2 SAMPLE OUTPUT

CHAPTER 8

8.0 CONCLUSION

In this paper, we ﬁrst reviewed the data transmission issues and the security issues in CWSNs. The deﬁciency of the symmetric key management for secure data transmission has been discussed. We then presented two secure and eﬃcient data transmission protocols respectively for CWSNs, SET-IBS and SET-IBOOS. In the evaluation section, we provided feasibility of the proposed SET-IBS and SET-IBOOS with respect to the security requirements and analysis against routing attacks. SET-IBS and SET-IBOOS are eﬃcient in communication and applying the ID-based crypto-system, which achieves security requirements in CWSNs, as well as solved the orphan node problem in the secure transmission protocols with the symmetric key management. Lastly, the comparison in the calculation and simulation results show that, the proposed SET-IBS and SET-IBOOS protocols have better performance than existing secure protocols for CWSNs. With respect to both computation and communication costs, we pointed out the merits that, using SET-IBOOS with less auxiliary security overhead is preferred for secure data transmission in CWSNs.

CHAPTER 9

9.0 REFERENCES

[1] H. Lu, J. Li, and H. Kameda, “A Secure Routing Protocol for Cluster-Based Wireless Sensor Networks Using ID-Based Digital Signature,” Proc. IEEE GLOBECOM, pp. 1-5, 2010.

[2] J. Sun et al., “An Identity-Based Security System for User Privacy in Vehicular Ad Hoc Networks,” IEEE Trans. Parallel & Distributed Systems, vol. 21, no. 9, pp. 1227-1239, Sept. 2010.

[3] D. Boneh and M. Franklin, “Identity-Based Encryption from the Weil Pairing,” Proc. 21st Ann. Int’l Cryptology Conf. Advances in Cryptology (CRYPTO ’01), pp. 213-229, 2001.

[4]K. Zhang, C. Wang, and C. Wang, “A Secure Routing Protocol for Cluster-Based Wireless Sensor Networks Using Group Key Management,” Proc. Fourth Int’l Conf. Wireless Comm., Networking and Mobile Computing (WiCOM), pp. 1-5, 2008.

[5] S. Sharma and S.K. Jena, “A Survey on Secure Hierarchical Routing Protocols in Wireless Sensor Networks,” Proc. Int’l Conf. Comm., Computing & Security (ICCCS), pp. 146-151, 2011.

Multicast Capacity in MANET with Infrastructure Support

22/10/201902/07/2019 by admin

MULTICAST CAPACITY IN MANET WITH INFRASTRUCTURE SUPPORT

PROJECT REPORT

Submitted to the Department of Computer Science & Engineering in the FACULTY OF ENGINEERING & TECHNOLOGY

In partial fulfillment of the requirements for the award of the degree

MASTER OF TECHNOLOGY

COMPUTER SCIENCE & ENGINEERING

APRIL 2015

BONAFIDE CERTIFICATE

Certified that this project report titled “MULTICAST CAPACITY IN MANET WITH INFRASTRUCTURE SUPPORT” is the bonafide work of Mr. _____________Who carried out the research under my supervision Certified further, that to the best of my knowledge the work reported herein does not form part of any other project report or dissertation on the basis of which a degree or award was conferred on an earlier occasion on this or any other candidate.

Signature of the Guide Signature of the H.O.D

Name Name

CHAPTER1

1.1 ABSTRACT:

We study the multicast capacity under a network model featuring both node’s mobility and infrastructure support. Combinations between mobility and infrastructure, as well as multicast transmission and infrastructure, have already been showed effective ways to increase it. In this work, we jointly consider the impact of the above three factors on network capacity.

We assume that m static base stations and n mobile users are placed in an ad hoc network. A general mobility model is adopted, such that each user moves within a bounded distance from its home-point with an arbitrary pattern. In addition, each mobile node serves as a source of multicast transmission, which results in a total number of n multicast transmissions.

We focus on the situations in which base stations actually benefit the capacity improvement, and find that multicast capacity in a mobile hybrid network falls into several regimes. For each regime, reachable upper and lower bounds are derived. Our work contains theoretical analysis of multicast capacity in hybrid networks and provides guidelines for the design of real hybrid system combing cellular and ad hoc networks.

1.2 INTRODUCTION:

Recent years witness a rapid development in wireless ad hoc networks, in both academic and industrial fields. Kumar and Gupta have showed in their ground breaking work that, even with the optimal scheduling, routing and relaying of packets, the per-node capacity still decreases as when n approaches the infinity. Many studies try to improve this disappointing scalability of throughput capacity by introducing different characteristics into ad hoc networks, such as mobility of nodes, an infrastructure of the network: a multicast transmission scheme.

Mobility in ad hoc networks was considered firstly by Tse. A store-carry-forward relaying scheme was proposed and proven to sustain a per-node capacity, if each node can visit the whole network area with an uniformly ergodic mobility process. Garetto et al. generalize the mobility model through a restriction that each moving node is located within a circle of radius 1/f(n). By mapping the network to a generalized random geometric graph, they have proven that per-node capacity is achievable.

Infrastructure in an ad hoc network provides a more straightforward increase to the capacity. Liu et al. claim that infrastructure can offer a linear capacity increase in a hybrid network, when the number of base stations increases asymptotically faster than . In addition, Kozat and Tassiulas prove that if the number of users served by each BS is bounded above, a per-node capacity of can be achieved. In Agarwal and Kumar further extend this result to .

Multicast transmission refers to the transmission from a single node to other k _ 1 nodes, so as to generalize both unicast and broadcast transmissions. In Li proves that multicast transmission can obtain a per-flow capacity of , which is larger than that of k unicast transmissions. The gain of multicast transmission results from a merge of relay paths within a minimum spanning tree. In Li et al. extend the multicast transmission to a Gaussian channel model and show similar capacity improvement under the corresponding protocol.

Many existing studies focus on the combinations of the above characteristics. Some aim to further increase the network performance, while others try to present a more realistic scenario. In Li et al. explore the multicast capacity in a static hybrid network with infrastructure support. Establishing a multicast tree with the help of infrastructure and employing a hybrid routing scheme, they have showed that the achievable multicast capacity in a hybrid network with m BSs is .On the other hand, Huang, Wang et al. study the unicast capacity of mobile hybrid networks and jointly consider the influences of node’s mobility and infrastructure support on it. A pernode capacity is for strong mobility, and for weak and trivial mobility.

In this paper, we further study the multicast capacity scaling laws of a mobile hybrid network characterizing both mobility and infrastructure. In our model, each of the n users moves around a home-point within a bounded radius. m wire-connected base stations are placed in a wireless ad hoc network, of which the area scales with n as f2(n) There are totally nc clusters with radius r = and the number of destinations in the multicast scheme is assumed as k. A multicast path can be generated with an infrastructure routing and a pure ad hoc routing, as well as a combination of both. Intuitively, in our hybrid routing scheme, we hope to circumvent the bottleneck of backbone transmission or wireless access for cellular networks and take the advantage of them, thus the capacity can be improved.

1.3 LITRATURE SURVEY

MULTICAST CAPACITY OF WIRELESS AD HOC NETWORKS

PUBLICATION: X.-Y. Li, IEEE/ACM Trans. Netw., vol. 17, no. 3, pp. 950-961, June 2009.

We study the multicast capacity of large-scale random extended multihop wireless networks, where a number of wireless nodes are randomly located in a square region with side length a = √n, by use of Poisson distribution with density 1. All nodes transmit at a constant power P , and the power decays with attenuation exponent α > 2. The data rate of a transmission is determined by the SINR as Blog(1+ SINR), where B is the bandwidth. There are ns randomly and independently chosen multicast sessions. Each multicast session has k randomly chosen terminals. We show that when k ≤ θ₁[(n)/((logn)^2α+
6)] and ns ≥ θ₂n^1/2+β, the capacity that each multicast session can achieve, with high probability, is at leastc₈[(√n)/(ns√k)], where θ₁, θ₂, and c₈ are some special constants and β > 0 is any positive real number. We also show that for k = O( [(n)/(log²n)]) , the per-flow multicast capacity under Gaussian channel is at most O([(√n)/(ns √k)]) when we have at least ns = Ω(logn) random multicast flows. Our result generalizes the unicast capacity for random networks using percolation theory.

MULTICAST CAPACITY OF WIRELESS AD HOC NETWORKS UNDER GAUSSIAN CHANNEL MODEL

PUBLICATION: X.-Y. Li, Y. Liu, S. Li, and S. Tang, IEEE/ACM Trans. Netw., vol. 18, no. 4, pp. 1145-1157, Aug. 2010.

MULTICAST CAPACITY FOR HYBRID WIRELESS NETWORKS

PUBLICATION: X. Mao, X.-Y. Li, and S. Tang, in Proc. ACM MobiHoc, Hong Kong, 2008, pp. 189-198.

We study the multicast capacity for hybrid wireless networks consisting of ordinary wireless nodes and base stations under Gaussian channel model, which generalizes both the unicast capacity and broadcast capacity for hybrid wireless networks. We simply consider the hybrid extended network, where the ordinary wireless nodes are placed in the square region A(n) with side-length radicn according to a Poisson point process with unit intensity. In addition, m additional base stations (BSs) serving as the relay gateway are placed regularly in the region A(n) and they are connected by a high-bandwidth wired network. Three broad categories of multicast strategies are proposed in this paper. According to the different scenarios in terms of m, n and n_d, we select the optimal scheme from the three categories of strategies, and derive the achievable multicast throughput based on the optimal decision.

CLOSING THE GAP OF MULTICAST CAPACITY FOR HYBRID WIRELESS NETWORKS

[4] S. Tang, X. Mao, T. Jung, J. Han, X.-Y. Li, B. Xu, and C. Ma, in Proc. ACM MobiHoc, Hilton Head, Italy, 2012,

pp. 135-144.

We study the multicast capacity of a random hybrid wireless network consisting of wireless terminals and base stations. Assume that n wireless terminals (nodes) are randomly deployed in a square region and all nodes have the uniform transmission range r and uniform interference range R = Θ(r); each wireless node can transmit/receive at Wa-bps. In addition, there are m base stations (neither source nodes nor receiver nodes) that are placed uniformly in this square region; each base station can communicate with adjacent base stations directly with a data rate WB-bps and the transmission rate between a base station and a wireless node is Wc-bps. Assume that there is a set of ns randomly selected nodes that will serve as the source nodes of ns multicast flows (each flow has randomly selected k−1 receivers). We found that the multicast capacity for hybrid networks has three regimes and for each of regimes, we derive the matching asymptotic upper and lower bounds of multicast capacity. Index Terms—Hybrid networks, capacity, multicast, broadcast. I.

CHAPTER 2

2.0 SYSTEM ANALYSIS

2.1 EXISTING SYSTEM:

Many existing studies focus on the combinations of the above characteristics. Some aim to further increase the network performance, while others try to present a more realistic scenario. In, Liet al. explores the multicast capacity in a static hybrid network with infrastructure support. Establishing a multicast tree with the help of infrastructure and employing a hybrid routing scheme, they have showed that the achievable multicast capacity in a hybrid network. On the other hand, Huang, Wanget al. study the unicast capacity of mobile hybrid networks and jointly consider the influences of node’s mobility and infrastructure support on it. A per-node capacity is for strong mobility, and for weak and trivial mobility.

2.1.1 DISADVANTAGES:

In a many existing systems the scalability is failure of throughput capacity and some of the failures in the mobility nodes, and in networks infrastructure.

2.2 PROPOSED SYSTEM:

In this paper, we further study the multicast capacity scaling laws of a mobile hybrid network characterizing both mobility and infrastructure. In our model, each of the n users moves around a home-point within a bounded radius. An m wire-connected base station is placed in a wireless ad hoc network, of which the area scales with n. There are totally n_c clusters with radius r and the number of destinations in the multicast scheme is assumed as k. A multicast path can be generated with an infrastructure routing and a pure ad hoc routing, as well as a combination of both. Intuitively, in our hybrid routing scheme, we hope to circumvent the bottleneck of backbone transmission or wireless access for cellular networks and take the advantage of them, thus the capacity can be improved.

2.2.1 ADVANTAGES:

Our work is the first one to consider the effect of a general mobility on multicast transmission. Furthermore, we study multicast capacity in a more realistic network model featuring both mobility and infrastructure support. As a result, our work generalizes both unicast and broadcast capacity results in MANETs and hybrid networks.
We can prove that mobility is trivial and the network acts as a static one.

2.3 HARDWARE & SOFTWARE REQUIREMENTS:

2.3.1 HARDWARE REQUIREMENT:

v Processor – Pentium –IV

Speed – 1.1 GHz
- RAM – 256 MB (min)
- Hard Disk – 20 GB
- Floppy Drive – 1.44 MB
- Key Board – Standard Windows Keyboard
- Mouse – Two or Three Button Mouse
- Monitor – SVGA

2.3.2 SOFTWARE REQUIREMENTS:

Operating System : Windows XP or Win7
Front End : Microsoft Visual Studio .NET 2008
Document : MS-Office 2007

CHAPTER 3

3.0 SYSTEM DESIGN:

Data Flow Diagram / Use Case Diagram / Flow Diagram:

The DFD is also called as bubble chart. It is a simple graphical formalism that can be used to represent a system in terms of the input data to the system, various processing carried out on these data, and the output data is generated by the system

The data flow diagram (DFD) is one of the most important modeling tools. It is used to model the system components. These components are the system process, the data used by the process, an external entity that interacts with the system and the information flows in the system.

DFD shows how the information moves through the system and how it is modified by a series of transformations. It is a graphical technique that depicts information flow and the transformations that are applied as data moves from input to output.

DFD is also known as bubble chart. A DFD may be used to represent a system at any level of abstraction. DFD may be partitioned into levels that represent increasing information flow and functional detail.

NOTATION:

SOURCE OR DESTINATION OF DATA:

External sources or destinations, which may be people or organizations or other entities

DATA SOURCE:

Here the data referenced by a process is stored and retrieved.

PROCESS:

People, procedures or devices that produce data. The physical component is not identified.

DATA FLOW:

Data moves in a specific direction from an origin to a destination. The data flow is a “packet” of data.

MODELING RULES:

There are several common modeling rules when creating DFDs:

All processes must have at least one data flow in and one data flow out.
All processes should modify the incoming data, producing new forms of outgoing data.
Each data store must be involved with at least one data flow.
Each external entity must be involved with at least one data flow.
A data flow must be attached to at least one process.

SYSTEM ARCHITECTURE:

DATAFLOW DIAGRAM

UML DIAGRAMS:

USECASE DIAGRAM:

CLASS DIAGRAM:

SEQUENCE DIAGRAM:

ACTIVITY DIAGRAM:

CHAPTER 4

4.0 IMPLEMENTATION:

In this section, we firstly provide a definition of a uniformly dense network, as well as some characteristics in such network. We show that when a network falls into strong mobility regime, it is equivalent to classify it as a uniformly dense network. Then reachable upper and lower bounds are presented in both pure ad hoc routing and cellular routing for uniformly dense networks. For pure ad hoc routing, we map the mobile network into a random geometric graph, and derive reachable capacity bounds. For cellular routing, we divide the routing scheme into three phases and achieve reachable upper and lower bounds in each phase, as well.

In the following part of this section, we will derive asymptotically reachable lower bound on multicast capacity in uniformly dense networks by ad hoc routing. We have already mapped a mobile network into a static graph, which makes the establishment of a multicast routing possible and realistic. We employ the next algorithm from to set up the multicast routing in graph. We consider the impact of infrastructure in multicast capacity of a mobile network. Multicast flows will be routed through BSs. We divide the bandwidth in air channels into uplink bandwidth WA and downlink bandwidth WC.

We further assume that the bandwidth of optical fibers connecting BSs is WB. Cellular routing RC consists of three phases. In the first phase, a multicast source node routes the packets to a BS. In the second phase, the packets are routed to the cells that contain destinations. In the last phase, BSs of these cells broadcast packets to the destinations. It is worth pointing out that such a routing cannot be established directly in mobile networks. However, with the help of the mapping scheme presented in the previous section, it is possible to generate a cellular multicast route in a random geometric graph.

4.1 ALGORITHM

4.2 MODULES:

MULTICAST CAPACITY:

SCHEDULING POLICIES:

HYBRID NETWORKS MOBILITY:

TRANSMISSION INFRASTRUCTURE:

COMMUNICATION AND INTERFERENCE:

4.3 MODULE DESCRIPTION:

MULTICAST CAPACITY:

Multicast capacity under a network model featuring both node’s mobility and infrastructure support between mobility and infrastructure, as well as multicast transmission and infrastructure, have already been shown effective ways to increase capacity. In this work, we jointly consider the impact of the above three factors on network capacity. We assume that m static base stations and n mobile users are placed in an ad hoc network, of which the area scales with n as f²(n). A general mobility model is adopted, such that each user moves within a bounded distance from its home point with an arbitrary pattern. In addition, each mobile node serves as the source of a multicast transmission, which results in a total number of n multicast transmissions. We focus on the situations that base stations actually benefit the capacity, and prove that multicast capacity of mobile hybrid network falls into three regimes. For each regime, matching upper and lower bounds are derived.

SCHEDULING POLICIES:

Scheduling is the method by which threads, processes or data flows are given access to system resources (e.g. processor time, communications bandwidth). This is usually done to load balance and share system resources effectively or achieve a target quality of service. The need for a scheduling algorithm arises from the requirement for most modern systems to perform multitasking (executing more than one process at a time) and multiplexing (transmit multiple data streams simultaneously across a single physical channel). A multicast path can be generated with an infrastructure routing and a pure ad hoc routing, as well as a combination of both. Intuitively, in our hybrid routing scheme, we hope to circumvent the bottleneck of backbone transmission or wireless access for cellular networks and take the advantage of them, thus the capacity can be improved.

HYBRID NETWORKS MOBILITY:

Further increase the network performance, while others try to present a more realistic scenario in the multicast capacity in a static hybrid network with infrastructure support. Establishing a multicast tree with the help of infrastructure and employing a hybrid routing scheme, they have showed that the achievable multicast capacity in a hybrid network with m BSs is

We further study the multicast capacity scaling laws of a mobile hybrid network characterizing both mobility and infrastructure. In our model, each of the n users moves around a home-point within a bounded radius. M wire-connected base stations are placed in a wireless ad hoc network, of which the area scales with n as f2n.

TRANSMISSION INFRASTRUCTURE:

We consider the effects of mobility and infrastructure in multicast capacity of a wireless mobile ad hoc network. We divide mobility into three regimes, and present reachable upper bounds and lower bounds for each regime. We assume that bandwidth is W for wireless channel, and WB for wired connections. In cellular routing, we further divide wireless frequency resource W into uplink bandwidth WA and downlink bandwidth WC.

COMMUNICATION AND INTERFERENCE:

Base stations communicate with each other through optical fiber with bandwidth WB. This kind of communication will not cause interference to themselves or wireless communications. We assume that the available bandwidth in all the wireless channels is W. In ad hoc routing, transmissions fully occupy the wireless bandwidth W. In cellular routing, bandwidth is further divided into uplink bandwidth WA and downlink bandwidth WC. All the communications in wireless channels are characterized by Protocol Model, which is defined as followed.

CHAPTER 5

5.0 SYSTEM STUDY:

5.1 FEASIBILITY STUDY:

Three key considerations involved in the feasibility analysis are

ECONOMICAL FEASIBILITY
TECHNICAL FEASIBILITY
SOCIAL FEASIBILITY

5.1.1 ECONOMICAL FEASIBILITY:

5.1.2 TECHNICAL FEASIBILITY

5.1.3 SOCIAL FEASIBILITY:

5.2 SYSTEM TESTING:

5.2.1 UNIT TESTING:

Description	Expected result
Test for application window properties.	All the properties of the windows are to be properly aligned and displayed.
Test for mouse operations.	All the mouse operations like click, drag, etc. must perform the necessary operations without any exceptions.

5.1.2 FUNCTIONAL TESTING:

Description	Expected result
Test for all modules.	All peers should communicate in the group.
Test for various peer in a distributed network framework as it display all users available in the group.	The result after execution should give the accurate result.

5.1. 3 NON-FUNCTIONAL TESTING:

Load testing
Performance testing
Usability testing
Reliability testing
Security testing

5.1.4 LOAD TESTING:

Description	Expected result
It is necessary to ascertain that the application behaves correctly under loads when ‘Server busy’ response is received.	Should designate another active node as a Server.

5.1.5 PERFORMANCE TESTING:

Description	Expected result
This is required to assure that an application perforce adequately, having the capability to handle many peers, delivering its results in expected time and using an acceptable level of resource and it is an aspect of operational management.	Should handle large input values, and produce accurate result in a expected time.

5.1.6 RELIABILITY TESTING:

Description	Expected result
This is to check that the server is rugged and reliable and can handle the failure of any of the components involved in provide the application.	In case of failure of the server an alternate server should take over the job.

5.1.7 SECURITY TESTING:

Description	Expected result
Checking that the user identification is authenticated.	In case failure it should not be connected in the framework.
Check whether group keys in a tree are shared by all peers.	The peers should know group key in the same group.

5.1.8 WHITE BOX TESTING:

Description	Expected result
Exercise all logical decisions on their true and false sides.	All the logical decisions must be valid.
Execute all loops at their boundaries and within their operational bounds.	All the loops must be finite.
Exercise internal data structures to ensure their validity.	All the data structures must be valid.

5.1.9 BLACK BOX TESTING:

Description	Expected result
To check for incorrect or missing functions.	All the functions must be valid.
To check for interface errors.	The entire interface must function normally.
To check for errors in a data structures or external data base access.	The database updation and retrieval must be done.
To check for initialization and termination errors.	All the functions and data structures must be initialized properly and terminated normally.

All the above system testing strategies are carried out in as the development, documentation and institutionalization of the proposed goals and related policies is essential.

CHAPTER 6

6.0 SOFTWARE DESCRIPTION:

6.1 JAVA TECHNOLOGY:

Java technology is both a programming language and a platform.

The Java Programming Language

The Java programming language is a high-level language that can be characterized by all of the following buzzwords:

Simple
- Architecture neutral
- Object oriented
- Portable
- Distributed
- High performance
- Interpreted
- Multithreaded
- Robust
- Dynamic
- Secure

6.2 THE JAVA PLATFORM:

The Java platform has two components:

The Java Virtual Machine (Java VM)
The Java Application Programming Interface (Java API)

You’ve already been introduced to the Java VM. It’s the base for the Java platform and is ported onto various hardware-based platforms.

The following figure depicts a program that’s running on the Java platform. As the figure shows, the Java API and the virtual machine insulate the program from the hardware.

6.3 WHAT CAN JAVA TECHNOLOGY DO?

The essentials: Objects, strings, threads, numbers, input and output, data structures, system properties, date and time, and so on.
Applets: The set of conventions used by applets.
Networking: URLs, TCP (Transmission Control Protocol), UDP (User Data gram Protocol) sockets, and IP (Internet Protocol) addresses.
Internationalization: Help for writing programs that can be localized for users worldwide. Programs can automatically adapt to specific locales and be displayed in the appropriate language.
Security: Both low level and high level, including electronic signatures, public and private key management, access control, and certificates.
Software components: Known as JavaBeans^TM, can plug into existing component architectures.
Object serialization: Allows lightweight persistence and communication via Remote Method Invocation (RMI).
Java Database Connectivity (JDBC^TM): Provides uniform access to a wide range of relational databases.

The Java platform also has APIs for 2D and 3D graphics, accessibility, servers, collaboration, telephony, speech, animation, and more. The following figure depicts what is included in the Java 2 SDK.

6.4 HOW WILL JAVA TECHNOLOGY CHANGE MY LIFE?

Get started quickly: Although the Java programming language is a powerful object-oriented language, it’s easy to learn, especially for programmers already familiar with C or C++.
Write less code: Comparisons of program metrics (class counts, method counts, and so on) suggest that a program written in the Java programming language can be four times smaller than the same program in C++.
Write better code: The Java programming language encourages good coding practices, and its garbage collection helps you avoid memory leaks. Its object orientation, its JavaBeans component architecture, and its wide-ranging, easily extendible API let you reuse other people’s tested code and introduce fewer bugs.
Develop programs more quickly: Your development time may be as much as twice as fast versus writing the same program in C++. Why? You write fewer lines of code and it is a simpler programming language than C++.
Avoid platform dependencies with 100% Pure Java: You can keep your program portable by avoiding the use of libraries written in other languages. The 100% Pure Java^TMProduct Certification Program has a repository of historical process manuals, white papers, brochures, and similar materials online.
Write once, run anywhere: Because 100% Pure Java programs are compiled into machine-independent byte codes, they run consistently on any Java platform.
Distribute software more easily: You can upgrade applets easily from a central server. Applets take advantage of the feature of allowing new classes to be loaded “on the fly,” without recompiling the entire program.

6.5 ODBC:

6.6 JDBC:

JDBC was announced in March of 1996. It was released for a 90 day public review that ended June 8, 1996. Because of user input, the final JDBC v1.0 specification was released soon after.

6.7 JDBC Goals:

The goals that were set for JDBC are important. They will give you some insight as to why certain classes and functionalities behave the way they do. The eight design goals for JDBC are as follows:

SQL Level API

SQL Conformance

JDBC must be implemental on top of common database interfaces

Provide a Java interface that is consistent with the rest of the Java system

Because of Java’s acceptance in the user community thus far, the designers feel that they should not stray from the current design of the core Java system.

Keep it simple

Use strong, static typing wherever possible

Strong typing allows for more error checking to be done at compile time; also, less error appear at runtime.

Keep the common cases simple

Finally we decided to precede the implementation using Java Networking.

And for dynamically updating the cache table we go for MS Access database.

Java ha two things: a programming language and a platform.

Java is a high-level programming language that is all of the following

Simple Architecture-neutral

Object-oriented Portable

Distributed High-performance

Interpreted Multithreaded

Robust Dynamic Secure

Compilation happens just once; interpretation occurs each time the program is executed. The figure illustrates how this works.

6.7 NETWORKING TCP/IP STACK:

The TCP/IP stack is shorter than the OSI one:

TCP is a connection-oriented protocol; UDP (User Datagram Protocol) is a connectionless protocol.

IP datagram’s:

UDP:

UDP is also connectionless and unreliable. What it adds to IP is a checksum for the contents of the datagram and port numbers. These are used to give a client/server model – see later.

TCP:

TCP supplies logic to give a reliable connection-oriented protocol above IP. It provides a virtual circuit that two processes can use to communicate.

Internet addresses

In order to use a service, you must be able to find it. The Internet uses an address scheme for machines so that they can be located. The address is a 32 bit integer which gives the IP address.

Network address:

Class A uses 8 bits for the network address with 24 bits left over for other addressing. Class B uses 16 bit network addressing. Class C uses 24 bit network addressing and class D uses all 32.

Subnet address:

Internally, the UNIX network is divided into sub networks. Building 11 is currently on one sub network and uses 10-bit addressing, allowing 1024 different hosts.

Host address:

8 bits are finally used for host addresses within our subnet. This places a limit of 256 machines that can be on the subnet.

Total address:

The 32 bit address is usually written as 4 integers separated by dots.

Port addresses

Sockets:

#include <sys/types.h>

#include <sys/socket.h>

int socket(int family, int type, int protocol);

6.8 JFREE CHART:

JFreeChart is a free 100% Java chart library that makes it easy for developers to display professional quality charts in their applications. JFreeChart’s extensive feature set includes:

A consistent and well-documented API, supporting a wide range of chart types;

A flexible design that is easy to extend, and targets both server-side and client-side applications;

Support for many output types, including Swing components, image files (including PNG and JPEG), and vector graphics file formats (including PDF, EPS and SVG);

JFreeChart is “open source” or, more specifically, free software. It is distributed under the terms of the GNU Lesser General Public Licence (LGPL), which permits use in proprietary applications.

6.8.1. Map Visualizations:

6.8.2. Time Series Chart Interactivity

6.8.3. Dashboards

6.8.4. Property Editors

CHAPTER 7

APPENDIX

7.1 SAMPLE SOURCE CODE

7.2 SAMPLE OUTPUT

CHAPTER 8

8.0 CONCLUSION:

This paper analyzes the multicast capacity in mobile ad hoc networks with infrastructure support. Hybrid routing schemes are proposed to achieve reachable upper and lower bounds in each of the regimes. It is worth pointing out that our work generalizes results in previous works on hybrid networks, impact of mobility and multicast transmissions, as well as any combinations of the above. Our results are instructive in the design of real hybrid system combining cellular and ad hoc networks.

CHAPTER 9

9.0 REFERENCES:

[1] X.-Y. Li, ‘‘Multicast Capacity of Wireless Ad Hoc Networks,’’IEEE/ACM Trans. Netw., vol. 17, no. 3, pp. 950-961, June 2009.

[2] X.-Y. Li, Y. Liu, S. Li, and S. Tang, ‘‘Multicast Capacity of Wireless Ad Hoc Networks under Gaussian Channel Model,’’ IEEE/ACM Trans. Netw., vol. 18, no. 4, pp. 1145-1157, Aug. 2010.

[3] X. Mao, X.-Y. Li, and S. Tang, ‘‘Multicast Capacity for Hybrid Wireless Networks,’’ in Proc. ACM MobiHoc, Hong Kong, 2008, pp. 189-198.

[4] S. Tang, X. Mao, T. Jung, J. Han, X.-Y. Li, B. Xu, and C. Ma,‘‘Closing the Gap of Multicast Capacity for Hybrid Wireless Networks,’’ in Proc. ACM MobiHoc, Hilton Head, Italy, 2012,

pp. 135-144.

[5] W. Huang, X. Wang, and Q. Zhang, ‘‘Capacity Scaling in Mobile Wireless Ad Hoc Network with Infrastructure Support,’’ in Proc. IEEE ICDCS, Genoa, Italy, 2010, pp. 848-857.

[6] Y. Guo, F. Hong, Z. Jin, Y. He, Y. Feng, and Y. Liu,‘‘Perpendicular Intersection: Locating Wireless Sensors with Mobile Beacon,’’ IEEE Trans. Veh. Technol., vol. 59, no. 7, pp. 3501-

3509, Sept. 2010.

[7] C. Wang, X.-Y. Li, S. Tang, C. Jiang, and Y. Liu, ‘‘Capacity and Delay in Mobile Ad Hoc Networks under Gaussian Channel Model,’’ SIGMOBILEMobile Comput. Commun. Rev., vol. 14, no. 3, pp. 22-24, July 2010.

Joint Routing and Medium Access Control in Fixed Random Access Wireless Multi hop Networks

22/10/201902/07/2019 by admin

Hop-by-Hop Message Authentication and Source Privacy in Wireless Sensor Networks

22/10/201902/07/2019 by admin

HOP-BY-HOP MESSAGE AUTHENTICATION AND SOURCE PRIVACY IN WIRELESS SENSOR NETWORKS

PROJECT REPORT

Submitted to the Department of Computer Science & Engineering in the FACULTY OF ENGINEERING & TECHNOLOGY

In partial fulfillment of the requirements for the award of the degree

MASTER OF TECHNOLOGY

COMPUTER SCIENCE & ENGINEERING

APRIL 2015

BONAFIDE CERTIFICATE

Certified that this project report titled “HOP-BY-HOP MESSAGE AUTHENTICATION AND SOURCE PRIVACY IN WIRELESS SENSOR NETWORKS” is the bonafide work of Mr. _____________Who carried out the research under my supervision Certified further, that to the best of my knowledge the work reported herein does not form part of any other project report or dissertation on the basis of which a degree or award was conferred on an earlier occasion on this or any other candidate.

Signature of the Guide Signature of the H.O.D

Name Name

CHAPTER 1

ABSTRACT:

Message authentication is one of the most effective ways to thwart unauthorized and corrupted messages from being forwarded in wireless sensor networks (WSNs). For this reason, many message authentication schemes have been developed, based on either symmetric-key cryptosystems or public-key cryptosystems. Most of them, however, have the limitations of high computational and communication overhead in addition to lack of scalability and resilience to node compromise attacks. To address these issues, a polynomial-based scheme was recently introduced. However, this scheme and its extensions all have the weakness of a built-in threshold determined by the degree of the polynomial: when the number of messages transmitted is larger than this threshold, the adversary can fully recover the polynomial.

In this paper, we propose a scalable authentication scheme based on elliptic curve cryptography (ECC). While enabling intermediate nodes authentication, our proposed scheme allows any node to transmit an unlimited number of messages without suffering the threshold problem. In addition, our scheme can also provide message source privacy. Both theoretical analysis and simulation results demonstrate that our proposed scheme is more efficient than the polynomial-based approach in terms of computational and communication overhead under comparable security levels while providing message source privacy.

INTRODUCTION:

MESSAGE authentication plays a key role in thwarting unauthorized and corrupted messages from being forwarded in networks to save the precious sensor energy. For this reason, many authentication schemes have been proposed in literature to provide message authenticity and integrity verification for wireless sensor networks (WSNs) .These schemes can largely be divided into two categories: public-key based approaches and symmetric-key based approaches. The symmetric-key based approach requires complex key management, lacks of scalability, and is not resilient to large numbers of node compromise attacks since the message sender and the receiver have to share a secret key. The shared key is used by the sender to generate a message authentication code (MAC) for each transmitted message. However, for this method, the authenticity and integrity of the message can only be verified by the node with the shared secret key, which is generally shared by a group of sensor nodes. An intruder can compromise the key by capturing a single sensor node.

In addition, this method does not work in multicast networks. To solve the scalability problem, a secret polynomial based message authentication scheme was introduced in. The idea of this scheme is similar to a threshold secret sharing, where the threshold is determined by the degree of the polynomial. This approach offers information-theoretic security of the shared secret key when the number of messages transmitted is less than the threshold. The intermediate nodes verify the authenticity of the message through a polynomial evaluation. However, when the number of messages transmitted is larger than the threshold, the polynomial can be fully recovered and the system is completely broken. An alternative solution was proposed in to thwart the intruder from recovering the polynomial by computing the coefficients of the polynomial. The idea is to add a random noise, also called a perturbation factor, to the polynomial so that the coefficients of the polynomial cannot be easily solved. However, a recent study shows that the random noise can be completely removed from the polynomial using error-correcting code techniques . For the public-key based approach, each message is transmitted along with the digital signature of the message generated using the sender’s private key. Every intermediate forwarder and the final receiver can authenticate the message using the sender’s public key. One of the limitations of the public-key based scheme is the high computational overhead. The recent progress on elliptic curve cryptography (ECC) shows that the public key schemes can be more advantageous in terms of key by capturing a single sensor node. In addition, this method does not work in multicast networks. To solve the scalability problem, a secret polynomial based message authentication scheme was introduced in. The idea of this scheme is similar to a threshold secret sharing, where the threshold is determined by the degree of the polynomial.

This approach offers information-theoretic security of the shared secret key when the number of messages transmitted is less than the threshold. The intermediate nodes verify the authenticity of the message through a polynomial evaluation. However, when the number of messages transmitted is larger than the threshold, the polynomial can be fully recovered and the system is completely broken. An alternative solution was proposed in to thwart the intruder from recovering the polynomial by computing the coefficients of the polynomial. The idea is to add a random noise, also called a perturbation factor, to the polynomial so that the coefficients of the polynomial cannot be easily solved. However, a recent study shows that the random noise can be completely removed from the polynomial using error-correcting code techniques. For the public-key based approach, each message is transmitted along with the digital signature of the message generated using the sender’s private key. Every intermediate forwarder and the final receiver can authenticate the message using the sender’s public key. One of the limitations of the public-key based scheme is the high computational overhead. The recent progress on elliptic curve cryptography (ECC) shows that the public key schemes can be more advantageous in terms of computational complexity, memory usage, and security resilience, since public-key based approaches have a simple and clean key management.

In this paper, we propose an unconditionally secure and efficient source anonymous message authentication (SAMA) scheme based on the optimal modified ElGamal signature (MES) scheme on elliptic curves. This MES scheme is secure against adaptive chosen-message attacks in the random oracle model. Our scheme enables the intermediate nodes to authenticate the message so that all corrupted message can be detected and dropped to conserve the sensor power. While achieving compromiseresiliency, flexible-time authentication and source identity protection, our scheme does not have the threshold problem. Both theoretical analysis and simulation results demonstrate that our proposed scheme is more efficient than the polynomial-based algorithms under comparable security levels.

The major contributions of this paper are the following: 1. We develop a source anonymous message authentication code (SAMAC) on elliptic curves that can provide unconditional source anonymity. 2. We offer an efficient hop-by-hop message authentication mechanism for WSNs without the threshold limitation. 3. We devise network implementation criteria on source node privacy protection in WSNs. 4. We propose an efficient key management framework to ensure isolation of the compromised nodes. 5. We provide extensive simulation results under ns-2 and TelosB on multiple security levels. To the best of our knowledge, this is the first scheme that provides hop-by-hop node authentication without the threshold limitation, and has performance better than the symmetric-key based schemes.

The distributed nature of our algorithm makes the scheme suitable for decentralized networks. The remainder of this paper is organized as follows: Section 2 presents the terminology and the preliminary that will be used in this paper. Section 3 discusses the related work, with a focus on polynomial-based schemes. Section 4 describes the proposed source anonymous message authentication scheme on elliptic curves. Section 5 discusses the ambiguity set (AS) selection strategies for source privacy. Section 6 describes key management and compromised node detection. Performance analysis and simulation results are provided in Section 7. We conclude in Section 8. through multi-hop communications. We assume there is a security server (SS) that is responsible for generation, storage and distribution of the security parameters among the network.

This server will never be compromised. However, after deployment, the sensor nodes may be captured and compromised by attackers. Once compromised, all information stored in the sensor nodes can be accessed by the attackers. The compromised nodes can be reprogrammed and fully controlled by the attackers. However, the compromised nodes will not be able to create new public keys that can be accepted by the SS and other nodes. Based on the above assumptions, this paper considers two types of attacks launched by the adversaries: Passive attacks. Through passive attacks, the adversaries could eavesdrop on messages transmitted in the network and perform traffic analysis. Active attacks. Active attacks can only be launched from the compromised sensor nodes. Once the sensor nodes are compromised, the adversaries will obtain all the information stored in the compromised nodes, including the security parameters of the compromised nodes. The adversaries can modify the contents of the messages, and inject their own messages.

LITRATURE SURVEY:

ATTACKING CRYPTOGRAPHIC SCHEMES BASED ON ‘PERTURBATION POLYNOMIALS

AUTHOR: M. Albrecht, C. Gentry, S. Halevi, and J. Katz,

PUBLISH: Report 2009/098, http://eprint.iacr.org/, 2009.

We show attacks on several cryptographic schemes that have recently been proposed for achieving various security goals in sensor networks. Roughly speaking, these schemes all use “perturbation polynomials” to add “noise” to polynomial-based systems that oer information- theoretic security, in an attempt to increase the resilience threshold while maintaining eciency. We show that the heuristic security arguments given for these modified schemes do not hold, and that they can be completely broken once we allow even a slight extension of the parameters beyond those achieved by the underlying information-theoretic schemes. Our attacks apply to the key predistribution scheme of Zhang et al. (MobiHoc 2007), the access-control schemes of Subramanian et al. (PerCom 2007), and the authentication schemes of Zhang et al. (INFOCOM 2008).

CRYPTOGRAPHIC KEY LENGTH RECOMMENDATION

PUBLISH: http://www.keylength.com/en/3/, 2013.

In most cryptographic functions, the key length is an important security parameter. Both academic and private organizations provide recommendations and mathematical formulas to approximate the minimum key size requirement for security. Despite the availability of these publications, choosing an appropriate key size to protect your system from attacks remains a headache as you need to read and understand all these papers.
This web site implements mathematical formulas and summarizes reports from well-known organizations allowing you to quickly evaluate the minimum security requirements for your system. You can also easily compare all these techniques and find the appropriate key length for your desired level of protection. The lengths provided here are designed to resist mathematic attacks; they do not take algorithmic attacks, hardware flaws, etc. into account.

LIGHTWEIGHT AND COMPROMISE-RESILIENT MESSAGE AUTHENTICATION IN SENSOR NETWORKS

AUTHOR: W. Zhang, N. Subramanian, and G. WangProc.

PUBLISH: IEEE INFOCOM, Apr. 2008.

Numerous authentication schemes have been proposed in the past for protecting communication authenticity and integrity in wireless sensor networks. Most of them however have following limitations: high computation or communication overhead, no resilience to a large number of node compromises, delayed authentication, lack of scalability, etc. To address these issues, we propose in this paper a novel message authentication approach which adopts a perturbed polynomial-based technique to simultaneously accomplish the goals of lightweight, resilience to a large number of node compromises, immediate authentication, scalability, and non-repudiation. Extensive analysis and experiments have also been conducted to evaluate the scheme in terms of security properties and system overhead.

COMPARING SYMMETRIC-KEY AND PUBLIC-KEY BASED SECURITY SCHEMES IN SENSOR NETWORKS: A CASE STUDY OF USER ACCESS CONTROL

AUTHOR: H. Wang, S. Sheng, C. Tan, and Q.

PUBLISH: Li Proc. IEEE 28th Int’l Conf. Distributed Computing Systems (ICDCS), pp. 11-18, 2008.

While symmetric-key schemes are efficient in processing time for sensor networks, they generally require complicated key management, which may introduce large memory and communication overhead. On the contrary, public-key based schemes have simple and clean key management, but cost more computational time. The recent progress of elliptic curve cryptography (ECC) implementation on sensors motivates us to design a public-key scheme and compare its performance with the symmetric-key counterparts. This paper builds the user access control on commercial off-the-shelf sensor devices as a case study to show that the public-key scheme can be more advantageous in terms of the memory usage, message complexity, and security resilience. Meanwhile, our work also provides insights in integrating and designing public-key based security protocols for sensor networks.

CHAPTER 2

EXISTING SYSTEM:

The public-key based approach, each message is transmitted along with the digital signature of the message generated using the sender’s private key. Every intermediate forwarder and the final receiver can authenticate the message using the sender’s public key. One of the limitations of the public-key based scheme is the high computational overhead.
Computational complexity, memory usage, and security resilience, since public-key based approaches have a simple and clean key management.

DISADVANTAGES OF EXISTING SYSTEM:

High computational and communication overhead.
Lack of scalability and resilience to node compromise attacks.
Polynomial-based scheme have the weakness of a built-in threshold determined by the degree of the polynomial.

PROPOSED SYSTEM:

We propose an unconditionally secure and efficient SAMA. The main idea is that for each message m to be released, the message sender, or the sending node, generates a source anonymous message authenticator for the message m.
The generation is based on the MES scheme on elliptic curves. For a ring signature, each ring member is required to compute a forgery signature for all other members in the AS.
In our scheme, the entire SAMA generation requires only three steps, which link all non-senders and the message sender to the SAMA alike. In addition, our design enables the SAMA to be verified through a single equation without individually verifying the signatures.

ADVANTAGES OF PROPOSED SYSTEM:

A novel and efficient SAMA based on ECC. While ensuring message sender privacy, SAMA can be applied to any message to provide message content authenticity.
To provide hop-by-hop message authentication without the weakness of the built- in threshold of the polynomial-based scheme, we then proposed a hop-by-hop message authentication scheme based on the SAMA.
When applied to WSNs with fixed sink nodes, we also discussed possible techniques for compromised node identification

HARDWARE & SOFTWARE REQUIREMENTS:

HARDWARE REQUIREMENT:

v Processor – Pentium –IV

Speed – 1.1 GHz
- RAM – 256 MB (min)
- Hard Disk – 20 GB
- Floppy Drive – 1.44 MB
- Key Board – Standard Windows Keyboard
- Mouse – Two or Three Button Mouse
- Monitor – SVGA

SOFTWARE REQUIREMENTS:

Operating System : Windows XP or Win7
Front End : Java JDK 1.7
Tools : Eclipse
Document : MS-Office 2007

CHAPTER 3

SYSTEM DESIGN:

Data Flow Diagram / Use Case Diagram / Flow Diagram:

The DFD is also called as bubble chart. It is a simple graphical formalism that can be used to represent a system in terms of the input data to the system, various processing carried out on these data, and the output data is generated by the system

The data flow diagram (DFD) is one of the most important modeling tools. It is used to model the system components. These components are the system process, the data used by the process, an external entity that interacts with the system and the information flows in the system.

DFD shows how the information moves through the system and how it is modified by a series of transformations. It is a graphical technique that depicts information flow and the transformations that are applied as data moves from input to output.

DFD is also known as bubble chart. A DFD may be used to represent a system at any level of abstraction. DFD may be partitioned into levels that represent increasing information flow and functional detail.

NOTATION:

SOURCE OR DESTINATION OF DATA:

External sources or destinations, which may be people or organizations or other entities

DATA SOURCE:

Here the data referenced by a process is stored and retrieved.

PROCESS:

People, procedures or devices that produce data. The physical component is not identified.

DATA FLOW:

Data moves in a specific direction from an origin to a destination. The data flow is a “packet” of data.

MODELING RULES:

There are several common modeling rules when creating DFDs:

All processes must have at least one data flow in and one data flow out.
All processes should modify the incoming data, producing new forms of outgoing data.
Each data store must be involved with at least one data flow.
Each external entity must be involved with at least one data flow.
A data flow must be attached to at least one process.

ARCHITECTURE DIAGRAM:

DATAFLOW DIAGRAM:

UML DIAGRAMS:

USE CASE DIAGRAM:

Client

Server

CLASS DIAGRAM:

SEQUENCE DIAGRAM:

Files Transmitted

ECC Encrypted Data

SAMA Verification

Checking for key

Data Received

ACTIVITY DIAGRAM:

CHAPTER 4

4.0 IMPLEMENTATION:

Privacy is sometimes referred to as anonymity. Communication anonymity in information management has been discussed in a number of previous works in generally refers to the state of being unidentifiable within a set of subjects. This set is called the AS. Sender anonymity means that a particular message is not linkable to any sender, and no message is linkable to a particular sender. We will start with the definition of the unconditionally secure SAMA.

4.1 ALGORITHM:

4.3 MODULES:

SERVER CLIENT MODULE:

KEY MANAGEMENT AND NODE DETECTION

SYMMETRIC-KEY CRYPTOSYSTEM

PUBLIC-KEY CRYPTOSYSTEM

HOP-BY-HOP AUTHENTICATION

4.4 MODULES DESCRIPTON:

SERVER CLIENT MODULE:

KEY MANAGEMENT AND NODE DETECTION:

Recently, message sender anonymity based on ring a signature was introduced in this approach enables the message sender to generate a source anonymous message signature with content authenticity assurance. To generate a ring signature, a ring member randomly selects an AS and forges a message signature for all other members. Then he uses his trap-door information to glue the ring together. The original scheme has very limited flexibility and very high complexity.

We focused on the cryptographic algorithm public-key based approach, each message is transmitted along with the digital signature of the message generated using the sender’s private key. Every intermediate forwarder and the final receiver can authenticate the message using the sender’s public key. The recent progress on ECC shows that the public-key schemes can be more advantageous in terms of memory usage, message complexity, and security resilience, since public-key based approaches have a simple and clean key management.

SYMMETRIC-KEY CRYPTOSYSTEM:

Symmetric key and hash based authentication schemes were proposed for WSNs. In these schemes, each symmetric authentication key is shared by a group of sensor nodes. An intruder can compromise the key by capturing a single sensor node. Therefore, these schemes are not resilient to node compromise attacks. Another type of symmetric-key scheme requires synchronization among nodes. These schemes, including TESLA and its variants, can also provide message sender authentication. However, this scheme requires initial time synchronization, which is not easy to be implemented in large scale WSNs. In addition, they also introduce delay in message authentication, and the delay increases as the network scales up.

PUBLIC-KEY CRYPTOSYSTEM:

A secret polynomial based message authentication scheme was introduced in scheme offers information- theoretic security with ideas similar to a threshold secret sharing, where the threshold is determined by the degree of the polynomial. When the number of messages transmitted is below the threshold, the scheme enables the intermediate node to verify the authenticity of the message through polynomial evaluation. However, when the number of messages transmitted is larger than the threshold, the polynomial can be fully recovered and the system is completely broken. To increase the threshold and the complexity for the intruder to reconstruct the secret polynomial, a random noise, also called a perturbation factor, was added to the polynomial in to thwart the adversary from computing the coefficient of the polynomial.

However, the added perturbation factor can be completely removed using error-correcting code techniques for the public-key based approach, each message is transmitted along with the digital signature of the message generated using the sender’s private key. Every intermediate forwarder and the final receiver can authenticate the message using the sender’s public key. The recent progress on ECC shows that the public-key schemes can be more advantageous in terms of memory usage, message complexity, and security resilience, since public-key based approaches have a simple and clean key management.

HOP-BY-HOP AUTHENTICATION:

Hop-by-hop authentication can be achieved through a public-key encryption system, the public-key based schemes were generally considered as not preferred, mainly due to their high computational overhead. However, our research demonstrates that it is not always true, especially for elliptic curve public-key cryptosystems.

In our scheme, each SAMA contains an AS of n randomly selected nodes that dynamically changes for each message. For n ¼ 1, our scheme can provide at least the same security as the bivariate polynomial-based scheme. For n > 1, we can provide extra source privacy benefits. Even if one message is corrupted, other messages transmitted in the network can still be secure.

Therefore, n can be much smaller than the parameters dx and dy. In fact, even a small n may provide adequate source privacy, while ensuring high system performance. In addition, in the bivariate polynomial-based scheme, there is only one base station that can send messages. All the other nodes can only act as intermediate nodes or receivers. This property makes the base station easy to attack, and severely narrows the applicability of this scheme. In fact, the major traffic inWSNs is packet delivery from the sensor nodes to the sink node.

Our scheme enables every node to transmit the message to the sink node as a message initiator.

The recent progress on ECC has demonstrated that the public-key based schemes have more advantages in terms of memory usage, message complexity, and security resilience, since public-key based approaches have a simple and clean key management.

CHAPTER 5

5.0 SYSTEM STUDY:

5.1 FEASIBILITY STUDY:

Three key considerations involved in the feasibility analysis are

ECONOMICAL FEASIBILITY
TECHNICAL FEASIBILITY
SOCIAL FEASIBILITY

5.1.1 ECONOMICAL FEASIBILITY:

5.1.2 TECHNICAL FEASIBILITY:

5.1.3 SOCIAL FEASIBILITY:

5.2 SYSTEM TESTING:

5.2.1 UNIT TESTING:

UNIT TESTING:

Description	Expected result
Test for application window properties.	All the properties of the windows are to be properly aligned and displayed.
Test for mouse operations.	All the mouse operations like click, drag, etc. must perform the necessary operations without any exceptions.

5.1.3 FUNCTIONAL TESTING:

FUNCTIONAL TESTING:

Description	Expected result
Test for all modules.	All peers should communicate in the group.
Test for various peer in a distributed network framework as it display all users available in the group.	The result after execution should give the accurate result.

5.1. 4 NON-FUNCTIONAL TESTING:

Load testing
Performance testing
Usability testing
Reliability testing
Security testing

5.1.5 LOAD TESTING:

Load Testing

Description	Expected result
It is necessary to ascertain that the application behaves correctly under loads when ‘Server busy’ response is received.	Should designate another active node as a Server.

5.1.5 PERFORMANCE TESTING:

PERFORMANCE TESTING:

Description	Expected result
This is required to assure that an application perforce adequately, having the capability to handle many peers, delivering its results in expected time and using an acceptable level of resource and it is an aspect of operational management.	Should handle large input values, and produce accurate result in a expected time.

5.1.6 RELIABILITY TESTING:

RELIABILITY TESTING:

Description	Expected result
This is to check that the server is rugged and reliable and can handle the failure of any of the components involved in provide the application.	In case of failure of the server an alternate server should take over the job.

5.1.7 SECURITY TESTING:

SECURITY TESTING:

Description	Expected result
Checking that the user identification is authenticated.	In case failure it should not be connected in the framework.
Check whether group keys in a tree are shared by all peers.	The peers should know group key in the same group.

5.1.7 WHITE BOX TESTING:

5.1.8 WHITE BOX TESTING:

Description	Expected result
Exercise all logical decisions on their true and false sides.	All the logical decisions must be valid.
Execute all loops at their boundaries and within their operational bounds.	All the loops must be finite.
Exercise internal data structures to ensure their validity.	All the data structures must be valid.

5.1.9 BLACK BOX TESTING:

5.1.10 BLACK BOX TESTING:

Description	Expected result
To check for incorrect or missing functions.	All the functions must be valid.
To check for interface errors.	The entire interface must function normally.
To check for errors in a data structures or external data base access.	The database updation and retrieval must be done.
To check for initialization and termination errors.	All the functions and data structures must be initialized properly and terminated normally.

All the above system testing strategies are carried out in as the development, documentation and institutionalization of the proposed goals and related policies is essential.

CHAPTER 6

6.0 SOFTWARE DESCRIPTION:

6.1 JAVA TECHNOLOGY:

Java technology is both a programming language and a platform.

The Java Programming Language

The Java programming language is a high-level language that can be characterized by all of the following buzzwords:

Simple
- Architecture neutral
- Object oriented
- Portable
- Distributed
- High performance
- Interpreted
- Multithreaded
- Robust
- Dynamic
- Secure

6.2 THE JAVA PLATFORM:

The Java platform has two components:

The Java Virtual Machine (Java VM)
The Java Application Programming Interface (Java API)

You’ve already been introduced to the Java VM. It’s the base for the Java platform and is ported onto various hardware-based platforms.

The following figure depicts a program that’s running on the Java platform. As the figure shows, the Java API and the virtual machine insulate the program from the hardware.

6.3 WHAT CAN JAVA TECHNOLOGY DO?

The essentials: Objects, strings, threads, numbers, input and output, data structures, system properties, date and time, and so on.
Applets: The set of conventions used by applets.
Networking: URLs, TCP (Transmission Control Protocol), UDP (User Data gram Protocol) sockets, and IP (Internet Protocol) addresses.
Internationalization: Help for writing programs that can be localized for users worldwide. Programs can automatically adapt to specific locales and be displayed in the appropriate language.
Security: Both low level and high level, including electronic signatures, public and private key management, access control, and certificates.
Software components: Known as JavaBeans^TM, can plug into existing component architectures.
Object serialization: Allows lightweight persistence and communication via Remote Method Invocation (RMI).
Java Database Connectivity (JDBC^TM): Provides uniform access to a wide range of relational databases.

The Java platform also has APIs for 2D and 3D graphics, accessibility, servers, collaboration, telephony, speech, animation, and more. The following figure depicts what is included in the Java 2 SDK.

6.4 HOW WILL JAVA TECHNOLOGY CHANGE MY LIFE?

Get started quickly: Although the Java programming language is a powerful object-oriented language, it’s easy to learn, especially for programmers already familiar with C or C++.
Write less code: Comparisons of program metrics (class counts, method counts, and so on) suggest that a program written in the Java programming language can be four times smaller than the same program in C++.
Write better code: The Java programming language encourages good coding practices, and its garbage collection helps you avoid memory leaks. Its object orientation, its JavaBeans component architecture, and its wide-ranging, easily extendible API let you reuse other people’s tested code and introduce fewer bugs.
Develop programs more quickly: Your development time may be as much as twice as fast versus writing the same program in C++. Why? You write fewer lines of code and it is a simpler programming language than C++.
Avoid platform dependencies with 100% Pure Java: You can keep your program portable by avoiding the use of libraries written in other languages. The 100% Pure Java^TMProduct Certification Program has a repository of historical process manuals, white papers, brochures, and similar materials online.
Write once, run anywhere: Because 100% Pure Java programs are compiled into machine-independent byte codes, they run consistently on any Java platform.
Distribute software more easily: You can upgrade applets easily from a central server. Applets take advantage of the feature of allowing new classes to be loaded “on the fly,” without recompiling the entire program.

6.5 ODBC:

6.6 JDBC:

JDBC was announced in March of 1996. It was released for a 90 day public review that ended June 8, 1996. Because of user input, the final JDBC v1.0 specification was released soon after.

6.7 JDBC Goals:

The goals that were set for JDBC are important. They will give you some insight as to why certain classes and functionalities behave the way they do. The eight design goals for JDBC are as follows:

SQL Level API

SQL Conformance

JDBC must be implemental on top of common database interfaces

Provide a Java interface that is consistent with the rest of the Java system

Because of Java’s acceptance in the user community thus far, the designers feel that they should not stray from the current design of the core Java system.

Keep it simple

Use strong, static typing wherever possible

Strong typing allows for more error checking to be done at compile time; also, less error appear at runtime.

Keep the common cases simple

Finally we decided to precede the implementation using Java Networking.

And for dynamically updating the cache table we go for MS Access database.

Java ha two things: a programming language and a platform.

Java is a high-level programming language that is all of the following

Simple Architecture-neutral

Object-oriented Portable

Distributed High-performance

Interpreted Multithreaded

Robust Dynamic Secure

Compilation happens just once; interpretation occurs each time the program is executed. The figure illustrates how this works.

6.7 NETWORKING TCP/IP STACK:

The TCP/IP stack is shorter than the OSI one:

TCP is a connection-oriented protocol; UDP (User Datagram Protocol) is a connectionless protocol.

IP datagram’s:

UDP:

UDP is also connectionless and unreliable. What it adds to IP is a checksum for the contents of the datagram and port numbers. These are used to give a client/server model – see later.

TCP:

TCP supplies logic to give a reliable connection-oriented protocol above IP. It provides a virtual circuit that two processes can use to communicate.

Internet addresses

In order to use a service, you must be able to find it. The Internet uses an address scheme for machines so that they can be located. The address is a 32 bit integer which gives the IP address.

Network address:

Class A uses 8 bits for the network address with 24 bits left over for other addressing. Class B uses 16 bit network addressing. Class C uses 24 bit network addressing and class D uses all 32.

Subnet address:

Internally, the UNIX network is divided into sub networks. Building 11 is currently on one sub network and uses 10-bit addressing, allowing 1024 different hosts.

Host address:

8 bits are finally used for host addresses within our subnet. This places a limit of 256 machines that can be on the subnet.

Total address:

The 32 bit address is usually written as 4 integers separated by dots.

Port addresses

Sockets:

#include <sys/types.h>

#include <sys/socket.h>

int socket(int family, int type, int protocol);

6.8 JFREE CHART:

JFreeChart is a free 100% Java chart library that makes it easy for developers to display professional quality charts in their applications. JFreeChart’s extensive feature set includes:

A consistent and well-documented API, supporting a wide range of chart types;

A flexible design that is easy to extend, and targets both server-side and client-side applications;

Support for many output types, including Swing components, image files (including PNG and JPEG), and vector graphics file formats (including PDF, EPS and SVG);

JFreeChart is “open source” or, more specifically, free software. It is distributed under the terms of the GNU Lesser General Public Licence (LGPL), which permits use in proprietary applications.

6.8.1. Map Visualizations:

6.8.2. Time Series Chart Interactivity

6.8.3. Dashboards

6.8.4. Property Editors

CHAPTER 7

APPENDIX

7.1 SAMPLE SOURCE CODE

7.2 SAMPLE OUTPUT

CHAPTER 8

8.1 CONCLUSION:

In this paper, we first proposed a novel and efficient SAMA based on ECC. While ensuring message sender privacy, SAMA can be applied to any message to provide message content authenticity. To provide hop-by-hop message authentication without the weakness of the builtin threshold of the polynomial-based scheme, we then proposed a hop-by-hop message authentication scheme based on the SAMA. When applied to WSNs with fixed sink nodes, we also discussed possible techniques for compromised node identification.

We compared our proposed scheme with the bivariate polynomial-based scheme through simulations using ns-2 and TelosB. Both theoretical and simulation results show that, in comparable scenarios, our proposed scheme is more efficient than the bivariate polynomial-based scheme in terms of computational overhead, energy consumption, delivery ratio, message delay, and memory consumption.

CHAPTER 9

REFERENCE:

[1] M. Albrecht, C. Gentry, S. Halevi, and J. Katz, “Attacking Cryptographic Schemes Based on ‘Perturbation Polynomials’,” Report 2009/098, http://eprint.iacr.org/, 2009.

[2] “Cryptographic Key Length Recommendation,” http://www.keylength.com/en/3/, 2013.

[3] W. Zhang, N. Subramanian, and G. Wang, “Lightweight and Compromise-Resilient Message Authentication in Sensor Networks,” Proc. IEEE INFOCOM, Apr. 2008.

[4] H. Wang, S. Sheng, C. Tan, and Q. Li, “Comparing Symmetric-Key and Public-Key Based Security Schemes in Sensor Networks: A Case Study of User Access Control,” Proc. IEEE 28th Int’l Conf. Distributed Computing Systems (ICDCS), pp. 11-18, 2008.

[5] Q. Liu, Y. Ge, Z. Li, H. Xiong, and E. Chen, “Personalized Travel Package Recommendation,” Proc. IEEE 11th Int’l Conf. Data Mining (ICDM ’11), pp. 407-416, 2011.

[6] Q. Liu, E. Chen, H. Xiong, C. Ding, and J. Chen, “Enhancing Collaborative Filtering by User Interests Expansion via Personalized Ranking,” IEEE Trans. Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 42, no. 1, pp. 218-233, Feb. 2012.

Developing Vehicular Data Cloud Services in the IoT Environment

22/10/201902/07/2019 by admin

Designing an Architecture for Monitoring Patients at Home Ontologies and Web Services for Clinical an

22/10/201902/07/2019 by admin

DESIGNING AN ARCHITECTURE FOR MONITORING PATIENTS AT HOME ONTOLOGIES AND WEB SERVICES FOR CLINICAL AND TECHNICAL MANAGEMENT INTEGRATION

PROJECT REPORT

Submitted to the Department of Computer Science & Engineering in the FACULTY OF ENGINEERING & TECHNOLOGY

In partial fulfillment of the requirements for the award of the degree

MASTER OF TECHNOLOGY

COMPUTER SCIENCE & ENGINEERING

APRIL 2015

CERTIFICATE

Certified that this project report titled “Designing an Architecture for Monitoring Patients at Home Ontologies and Web Services for Clinical and Technical Management Integration” is the bonafide work of Mr. _____________Who carried out the research under my supervision Certified further, that to the best of my knowledge the work reported herein does not form part of any other project report or dissertation on the basis of which a degree or award was conferred on an earlier occasion on this or any other candidate.

Signature of the Guide Signature of the H.O.D

Name Name

DECLARATION

I hereby declare that the project work entitled “Designing an Architecture for Monitoring Patients at Home Ontologies and Web Services for Clinical and Technical Management Integration” Submitted to BHARATHIDASAN UNIVERSITY in partial fulfillment of the requirement for the award of the Degree of MASTER OF SCIENCE IN COMPUTER SCIENCE is a record of original work done by me the guidance of Prof.A.Vinayagam M.Sc., M.Phil., M.E., to the best of my knowledge, the work reported here is not a part of any other thesis or work on the basis of which a degree or award was conferred on an earlier occasion to me or any other candidate.

(Student Name)

(Reg.No)

Place:

Date:

ACKNOWLEDGEMENT

I am extremely glad to present my project “Designing an Architecture for Monitoring Patients at Home Ontologies and Web Services for Clinical and Technical Management Integration” which is a part of my curriculum of third semester Master of Science in Computer science. I take this opportunity to express my sincere gratitude to those who helped me in bringing out this project work.

I would like to express my Director, Dr. K. ANANDAN, M.A.(Eco.), M.Ed., M.Phil.,(Edn.), PGDCA., CGT., M.A.(Psy.) of who had given me an opportunity to undertake this project.

I am highly indebted to Co-Ordinator Prof. Muniappan Department of Physics and thank from my deep heart for her valuable comments I received through my project.

I wish to express my deep sense of gratitude to my guide
Prof. A.Vinayagam M.Sc., M.Phil., M.E., for her immense help and encouragement for successful completion of this project.

I also express my sincere thanks to the all the staff members of Computer science for their kind advice.

And last, but not the least, I express my deep gratitude to my parents and friends for their encouragement and support throughout the project.

CHAPTER 1

ABSTRACT:

This paper presents the design and implementation of an architecture based on the combination of ontologies, rules, web services, and the autonomic computing paradigm to manage data in home-based telemonitoring scenarios.

The architecture includes two layers: 1) a conceptual layer and 2) a data and communication layer. On the one hand, the conceptual layer based on ontologies is proposed to unify the management procedure and integrate incoming data from all the sources involved in the telemonitoring process. On the other hand, the data and communication layer based on REST web service (WS) technologies is proposed to provide practical backup to the use of the ontology, to provide a real implementation of the tasks it describes and thus to provide a means of exchanging data (support communication tasks).

We study regarding chronic obstructive pulmonary disease data management is presented in order to evaluate the efficiency of the architecture. This proposed ontology-based solution defines a flexible and scalable architecture in order to address main challenges presented in home-based telemonitoring scenarios and thus provide a means to integrate, unify, and transfer data supporting both clinical and technical management tasks.

1.2 INTRODUCTION

Patient empowerment is considered as a philosophy of health care based on the perspective that better outcomes are achieved when patients become active participants in their own health management. This new paradigm is a central idea in the European Union (EU) health strategy supported by international health organizations including the World Health Organization among others, and its effectiveness in yielding quality of care is an obvious and essential area of research. This new idea invites to look for new ways of providing healthcare, e.g., by using information and communications technologies. In this context, home-based telemonitoring systems can be used as self-care management tools, while collaborative processes among healthcare personnel and patients are maintained, thus the patient’s safe control is guaranteed. Telemonitoring systems face the problem of delivering medicine to the current growing population with chronic conditions while at the same time covering the dimensions of quality of care and new paradigms such as empowerment can be supported.

By periodically collecting patients’ themselves clinical data (located at their home sites) and transferring them to physicians located in remote sites, patient’s health status supervision and feedback provision are possible. This type of telemedicine system guarantees patient control while reducing costs and avoiding hospital overflows. These two sites (home site and healthcare site) comprised a typical home-based telemonitoring system. At home site, data acquired by using MDs together with the patient’s feedback are collected in a concentrator device (HG) used to evaluate and/or transfer the acquired data outside the patient’s home if necessary. At the health-care site, a server device is used to manage information from the home site as well as to manage and store the patient’s monitoring guidelines defined by physicians (TS, telemonitoring server). In fact, this telemonitoring process, and consequently the evolution of the patient’s health status, ismanaged through the indications or monitoring guidelines provided by physicians.

Although significant contributions have been made in this field in recent decades, telemedicine and in e-health scenarios in general still pose numerous challenges that need to be addressed by researchers in order to take maximum advantage of the benefits that these systems provide and to support their long-term implementation. Interoperability and integration are critical challenges that also need to be addressed when developing monitoring systems in order to provide effective healthcare and to make possible seamless communication among the different heterogeneous health entities that participate in the monitoring process. This integration should be addressed at both end sites of the scenario but also in the communication link, thus integrating the way of transferring and exchanging information efficiently between them.

We providing personalized care services and taking into account the patient’s context have been identified as additional requirements. Furthermore, apart from clinical data aspects, technical issues should be also addressed in this scenario. Technical management of all the devices that comprise the telemonitoring scenario (e.g., the MDs and HG) is an important task that may or may not be integrated under the same architecture as clinical management. Hence, at this technical level, research is still required to address these challenges. Consequently there is a need for the development of new telemonitoring architectures.

Great efforts have been made in recent years in developing standards to deal with interoperability at different points of the e-health communication infrastructure such as the ISO/IEEE 11073 (X73) for MDs interoperability, the OpenEHR initiative for storage, management and retrieval of electronic health record (EHR) information or as the standardized Health Level Seven7 (HL7) messages to solve clinical data transferences. Nevertheless, additional efforts are required to enable them to work together and ultimately provide a higher level of integration.

Specifically, in this telemonitoring scenario, there is not a unique standard-based solution to address data and management integration. Since several standards can be used (some of them in combination with proprietary protocols or other standards) at different points of this scenario, the interoperability problem remains unsolved unless these standards would merge into one or alignments and combination of them would be done. According to Berges et al. interoperability does not mean to have a unique representation but a semantically acknowledged equivalent one. That is the reason to propose in this study an ontology-based architecture in order to provide with a common knowledge about the exchanged data and the management of such data. This ontology constitutes the knowledge equivalent one. Then, at both ends of the architecture other standards could be used for other managing purposes relating this model with the specific desired approach. Using this alternative, a knowledge model is first provided that avoids alignment of models two by two, while all being related through the main ontology.

Ontologies-based solutions have been popularized over the past few years. Ontologies provide a higher level of abstraction and have been successfully used in telemonitoring scenarios and other areas to provide knowledge representation and semantic integration, thus a common understanding about data exchanged by all the entities. Furthermore, its combination with rules allows providing personalized management services and thus personalized care. Although there are works that describe the details of an ontology approach in this domain, they do not devote much attention to the architecture implementation and the communication used to exchange the information described. Consequently, fewworks have given details about this practical implementation of the ontology-based system which may be of interest for the development of other ontology-based applications in and outside the e-health domain.

This paper presents an ontology-driven architecture to integrate data management and enable its communication in a telemonitoring scenario. The proposed architecture includes two layers: the conceptual layer (the ontology) and the communication and data layer. The conceptual layer uses the HOTMES and its extensions introduced. Specifically, the OWL-DL language was selected to define this ontology model. The second layer is based on WS technologies. WSs have been successfully used in network management and also in other works to exchange data modeled by ontology. However, our proposal, inspired on the representational state transfer (REST) style and based on a generic communication method, provides a different design approach that may be reusable for other systems based on ontologies. Furthermore, security issues have been considered. The aim is to define a flexible and scalable architecture in order to address main challenges presented in home-based telemonitoring scenarios and thus provide a means to integrate and transfer data supporting both clinical and technical data management.

1.3 LITRATURE SURVEY

AUTHOR AND PUBLICATION: JD. Trigo, I. Mart´ınez, A. Alesanco, A. Kollmann, J. Escayola, D. Hayn, G. Schreier, and J. Garc´ıa, “AN INTEGRATED HEALTHCARE INFORMATION SYSTEM FOR END-TO-END STANDARDIZED EXCHANGE AND HOMOGENEOUS MANAGEMENT OF DIGITAL ECG FORMATS,” IEEE Trans. Inf. Technol. Biomed., vol. 16, no. 4, pp. 518–529, Jul. 2012.

EXPLANATION:

This paper investigates the application of the enterprise information system (EIS) paradigm to standardized cardiovascular condition monitoring. There are many specifications in cardiology, particularly in the ECG standardization arena. The existence of ECG formats, however, does not guarantee the implementation of homogeneous, standardized solutions for ECG management. In fact, hospital management services need to cope with various ECG formats and, moreover, several different visualization applications. This heterogeneity hampers the normalization of integrated, standardized healthcare information systems, hence the need for finding an appropriate combination of ECG formats and suitable EIS-based software architecture that enables standardized exchange and homogeneous management of ECG formats. Determining such a combination is one objective of this paper.

We develop the integrated healthcare information system that satisfies the requirements posed by the previous determination. The ECG formats selected include ISO/IEEE11073, Standard Communications Protocol for Computer-Assisted Electrocardiography, and an ECG ontology. The EIS-enabling techniques and technologies selected include web services, simple object access protocol, extensible markup language, or business process execution language. Such a selection ensures the standardized exchange of ECGs within, or across, healthcare information systems while providing modularity and accessibility.

AUTHOR AND PUBLICATION: D. Ria˜no, F. Real, J. A. L´opez-Vallverd´u, F. Campana, S. Ercolani, P. Mecocci, R. Annicchiarico, and C. Caltagirone, “AN ONTOLOGY-BASED PERSONALIZATION OF HEALTH-CARE KNOWLEDGE TO SUPPORT CLINICAL DECISIONS FOR CHRONICALLY ILL PATIENTS,” J. Biomed. Informat., vol. 45, no. 3, pp. 429–446, 2012.

EXPLANATION:

Chronically ill patients are complex health care cases that require the coordinated interaction of multiple professionals. A correct intervention of these sort of patients entails the accurate analysis of the conditions of each concrete patient and the adaptation of evidence-based standard intervention plans to these conditions. There are some other clinical circumstances such as wrong diagnoses, unobserved comorbidities, missing information, unobserved related diseases or prevention, whose detection depends on the capacities of deduction of the professionals involved. In this paper, we introduce ontology for the care of chronically ill patients and implement two personalization processes and a decision support tool. The first personalization process adapts the contents of the ontology to the particularities observed in the health-care record of a given concrete patient, automatically providing a personalized ontology containing only the clinical information that is relevant for health-care professionals to manage that patient. The second personalization process uses the personalized ontology of a patient to automatically transform intervention plans describing health-care general treatments into individual intervention plans. For comorbid patients, this process concludes with the semi-automatic integration of several individual plans into a single personalized plan. Finally, the ontology is also used as the knowledge base of a decision support tool that helps health-care professionals to detect anomalous circumstances such as wrong diagnoses, unobserved comorbidities, missing information, unobserved related diseases, or preventive actions. Seven health-care centers participating in the K4CARE project, together with the group SAGESA and the Local Health System in the town of Pollenza have served as the validation platform for these two processes and tool. Health-care professionals participating in the evaluation agree about the average quality 84% (5.9/7.0) and utility 90% (6.3/7.0) of the tools and also about the correct reasoning of the decision support tool, according to clinical standards.

AUTHOR AND PUBLICATION: I.Berges, J. Bermudez, and A. Illarramendi, “TOWARDS SEMANTIC INTEROPERABILITY OF ELECTRONIC HEALTH RECORDS,” IEEE Trans. Inf. Technol. Biomed., vol. 16, no. 3, pp. 424–431, May 2012.

EXPLANATION:

Although the goal of achieving semantic interoperability of electronic health records (EHRs) is pursued by many researchers, it has not been accomplished yet. In this paper, we present a proposal that smoothes out the way toward the achievement of that goal. In particular, our study focuses on medical diagnoses statements. In summary, the main contributions of our ontology-based proposal are the following: first, it includes a canonical ontology whose EHR-related terms focus on semantic aspects. As a result, their descriptions are independent of languages and technology aspects used in different organizations to represent EHRs. Moreover, those terms are related to their corresponding codes in well-known medical terminologies. Second, it deals with modules that allow obtaining rich ontological representations of EHR information managed by proprietary models of health information systems. The features of one specific module are shown as reference. Third, it considers the necessary mapping axioms between ontological terms enhanced with so-called path mappings. This feature smoothes out structural differences between heterogeneous EHR representations, allowing proper alignment of information.

AUTHOR AND PUBLICATION: N. Lasierra,A.Alesanco, J.Garc´ıa, andD.O’Sullivan, “DATA MANAGEMENT IN HOME SCENARIOS USING AN AUTONOMIC ONTOLOGY-BASED APPROACH,” in Proc. of the 9th IEEE Int. Conf. Pervasive Workshop on Manag. Ubiquitous Commun. Services part of PerCom, 2012, pp. 94–99.

EXPLANATION:

An ontology-based approach to deal with data and management procedure integration in home-based scenarios is presented in this paper. The proposed ontology not only provides a means to represent exchanged data but also to unify the way of accessing, controlling, evaluating and transferring information remotely. The structure of this ontology has been inspired by the autonomic computing paradigm, thus it describes the tasks that comprise the MAPE (Monitor, Analyze, Plan and Execute) process. Furthermore the use of SPARQL (Simple Protocol and RDF Query Language) is proposed in this paper to express conditions and rules that determine the performance of these tasks according to each situation. Finally two practical application cases of the proposed ontology-based approach are presented.

CHAPTER 2

2.0 SYSTEM ANALYSIS

2.1 EXISTING SYSTEM:

Telemonitoring systems face the problem of delivering medicine to the current growing population with chronic conditions while at the same time covering the dimensions of quality of care and new paradigms such as empowerment can be supported. By periodically collecting patients’ themselves clinical data (located at their home sites) and transferring them to physicians located in remote sites, patient’s health status supervision and feedback provision are possible.

This type of telemedicine system guarantees patient control while reducing costs and avoiding hospital overflows. These two sites (home site and healthcare site) comprised a typical home-based telemonitoring system. At home site, data acquired by using MDs together with the patient’s feedback are collected in a concentrator device (HG) used to evaluate and/or transfer the acquired data outside the patient’s home if necessary.

2.1.1 DISADVANTAGES:

Existing models for chronic diseases pose several technology-oriented challenges for home-based care, where assistance services rely on a close collaboration among different stakeholders, such as health operators, patient relatives, and social community members.

An ontology-based context model and a related context management system providing a configurable and extensible service-oriented framework to ease the development of applications for monitoring and handling patient chronic conditions.

The system has been developed in a prototypal version, and integrated with a service platform for supporting operators of home-based care networks in cooperating and sharing patient-related information and coordinating mutual interventions for handling critical and alarm situations.

2.2 PROPOSED SYSTEM:

We present an ontology-driven architecture to integrate data management and enable its communication in a telemonitoring scenario. It enables to not only integrate patient’s clinical data management but also technical data management of all devices that are included in the scenario. The proposed architecture includes two layers: the conceptual layer (the ontology) and the communication and data layer.

The conceptual layer uses the HOTMES and its extensions introduced specifically in the OWL-DL language was selected to define this ontology model. The second layer is based on WS technologies. WSs have been successfully used in network management and also in other works to exchange data modeled by ontology is our proposal, inspired on the representational state transfer (REST) style and based on a generic communication method, provides a different design approach that may be reusable for other systems based on ontologies.

Furthermore, security issues have been considered. The aim is to define a flexible and scalable architecture in order to address main challenges presented in home-based telemonitoring scenarios and thus provide a means to integrate and transfer data supporting both clinical and technical data management.

2.2.1 ADVANTAGES:

Ontologies provide a higher level of abstraction and have been successfully used in telemonitoring scenarios and other areas to provide knowledge representation and semantic integration, thus a common understanding about data exchanged by all the entities. Furthermore, its combination with rules allows providing personalized management services and thus personalized care.

We describe the details of an ontology approach in this domain, they do not devote much attention to the architecture implementation and the communication used to exchange the information described.

Our implementation of the ontology-based system which may be of interest for the development of other ontology-based applications in and outside the e-health domain the ontology for interpreting the data transferred for the communication of end sources of the architecture. The data and communication layer deals with data management and transmission.

2.3 HARDWARE & SOFTWARE REQUIREMENTS:

2.3.1 HARDWARE REQUIREMENT:

v Processor – Pentium –IV

Speed – 1.1 GHz
- RAM – 256 MB (min)
- Hard Disk – 20 GB
- Floppy Drive – 1.44 MB
- Key Board – Standard Windows Keyboard
- Mouse – Two or Three Button Mouse
- Monitor – SVGA

2.3.2 SOFTWARE REQUIREMENTS:

Operating System : Windows XP or Win7
Front End : JAVA JDK 1.7
Back End : MYSQL Server
Server : Apache Tomact Server
Script : JSP Script
Document : MS-Office 2007

CHAPTER 3

3.0 SYSTEM DESIGN:

Data Flow Diagram / Use Case Diagram / Flow Diagram:

The DFD is also called as bubble chart. It is a simple graphical formalism that can be used to represent a system in terms of the input data to the system, various processing carried out on these data, and the output data is generated by the system

The data flow diagram (DFD) is one of the most important modeling tools. It is used to model the system components. These components are the system process, the data used by the process, an external entity that interacts with the system and the information flows in the system.

DFD shows how the information moves through the system and how it is modified by a series of transformations. It is a graphical technique that depicts information flow and the transformations that are applied as data moves from input to output.

DFD is also known as bubble chart. A DFD may be used to represent a system at any level of abstraction. DFD may be partitioned into levels that represent increasing information flow and functional detail.

NOTATION:

SOURCE OR DESTINATION OF DATA:

External sources or destinations, which may be people or organizations or other entities

DATA SOURCE:

Here the data referenced by a process is stored and retrieved.

PROCESS:

People, procedures or devices that produce data’s in the physical component is not identified.

DATA FLOW:

Data moves in a specific direction from an origin to a destination. The data flow is a “packet” of data.

MODELING RULES:

There are several common modeling rules when creating DFDs:

All processes must have at least one data flow in and one data flow out.
All processes should modify the incoming data, producing new forms of outgoing data.
Each data store must be involved with at least one data flow.
Each external entity must be involved with at least one data flow.
A data flow must be attached to at least one process.

3.1 ARCHITECTURE DIAGRAM

3.2 DATAFLOW DIAGRAM

ADMIN:

USER:

UML DIAGRAMS:

3.2 USE CASE DIAGRAM:

3.3 SEQUENCE DIAGRAM:

3.5 ACTIVITY DIAGRAM:

CHAPTER 4

4.0 IMPLEMENTATION:

ONTOLOGIES:

According to one of the most widely accepted definitions of ontologies in computer science, ontology can be described as “an explicit and formal specification of a shared conceptualization”. In simple words, ontologies represent concepts and basic relationships for the purpose of comprehension of a common knowledge area. To develop an ontology means to formalize a common view of a certain domain.

1) OWL Language: In computer science, there are plenty of formal languages that can be used to define and constructontologies. These languages allow encoding knowledge contained in ontology in a simple and formal way. However, the standardized RDF and OWL have been gaining popularity in the semantic web world. Ontology can be formally described in OWL using following basic elements: 1) classes; 2) individuals; and 3) properties. These elements are used in order to describe concepts, instances, or members of a class and relationships between individuals of two classes (object properties) or to link individuals with datatype values, respectively (data type properties). Apart from these basic elements OWL provides with class descriptors used to precisely describe OWL classes which includes properties restrictions (value and cardinality constraints), class axioms, properties axioms, and properties over individuals.

2) Rules: Generally, ontology-based solutions combine knowledge presented in ontologies with dynamic knowledge presented by the use of rules. A system based on the use of rules usually contains a set of if-then rules (which indicate what should be done according to a situation) and a rule engine used to apply them. By using rules, the behavior of individuals can be expressed inside a domain. Hence, they can be used to generate new knowledge and can also be used to provide personalized services. One of the most popular languages for rules definition is SWRL.

However, in our study, we used SPARQL to define some rules is a query language it can be used as a rule language by combining CONSTRUCT clause and FILTER restrictions. On the one hand, the CONSTRUCT query form returns a single RDF graph built based on the results of matching with the graph pattern of the query and by taking the specified graph template. On the other hand, the FILTER clause can be used to restrict solutions to those which the filter expression considers as TRUE. Only if the filter function evaluates to true is the solution to be included in the solution sequence. Note that although this language was good enough for our purpose, its limitations should be studied for other purposes (e.g., recursive tasks) and the adequacy of SWRL could be studied for complex applications.

WEB SERVICES

Web services are used in this study as software technology to access and exchange information modeled by the ontology. According to the W3C, a WS is a “software system designed to support interoperable machine-to-machine interaction over a communication network”. Systems may interact with the web services by exchanging SOAP messages serialized in XML for its message format and sent over other application layer protocols, usually HTTP. Although SOAP-based web services are the most popular types of WSs, there are other styles of programming a WS such as the REST style.

1) Rest Style for DesigningWeb Services: REST is a style of software architecture for distributed hypermedia systems such as the World Wide Web first defined in 2000 by Fielding. This style is based on the idea of transferring the representations of resources, a resource being any item of interest. One of the key advantages of the REST architecture are scalability of components and generality of interfaces. Although REST was initially described in the context of HTTP, this paradigm can be applied to other protocols or implementations. Web services can also be described using this style. A WS implemented using HTTP and the principles of REST architecture is designated as REST(ful) WS. Requests made from the client and responses from the WS are used to transfer resources information. Each resource is identified through an URI. Stateless behavior of data using XML and/or JSON and explicitly used HTTP methods (PUT, GET, POST, DELETE) to exchange resources are the key characteristics of a REST(ful) WS.

4.1 MODULES:

MANAGEMENT PROFILE:

DATA AND COMMUNICATION LAYER:

HG AND TS MANAGEMENT MODULES:

COMMUNICATION FLOW AND WORKFLOW:

4.3 MODULE DESCRIPTION:

CLINICAL MANAGEMENT PROFILE:

COPD patients were identified as candidates to be monitored at home sites. From a clinical point of view, it was an interesting case study (some estimations suggest that up to 10% of the European population suffers COPD). From a technical point of view, the case of the COPD patient led to define a complex technical management profile (because different MDs are required to be used by the patient) and interesting option to test the performance of the agent. Hence, one patient profile was designed according to the clinical HOTMES ontology and one technical management profile was designed according to the technical HOTMES ontology.

The patient profile includes the required tasks to monitor a COPD patient such as controlling the FEV1 measurement in order to detect the presence and severity of the airway obstruction. It was configured by a primary care physician by means of published clinical guidelines in patient profile included 15 monitoring task, 11 analysis task, 9 planning task, and 3 execution task. This configuration led to include 144 new instances and to configure 18 rules. The details of this profile and its evaluation to configure other type of profiles can be technical management profile was designed to monitor the state of theMDs used by the COPD patient (weighing scale, a blood pressure monitor, a pulse-oximeter, and a glucometer) and the consumption of resources of the correspondent HG. In addition rules were configured and 83 new instances were required to be configured in the technical management profile in additional information of the application of the HOTMES ontology for technical tasks.

DATA AND COMMUNICATION LAYER:

In the data layer, the communication between the end sites is established using WS technologies. Consequently, a WS has been designed to be placed in the TS and also a web client to be installed in the HG (to establish a communication with the TS). This communication allows the HG to ask for its associated management profile to the TS and to transmit acquired information from the HG to the TS.

A REST WS was developed in order to enhance the scalability and flexibility of the architecture and improve the performance (efficiency). This WS comprises and defines a set of operations over the following resources: an OWL ontology, the rules (transferred by means of an XML), OWL individuals (sent by the IndividualWS structure), properties datatype values corresponding to an individual (identified by the URI of the individual and the URI of the property sent in a string generic type), and inform messages to provide some control functions to the web pair communication.

Each one of these resources was identified by an URI, and a set of operations was defined for each particular resource using HTTP methods (e.g., GET or PUT). This WS interface allows information described in the ontology to be exchanged in a generic manner. This is one key that contributes to the reusability and easy extension of the architecture. Described communication methods do not depend on the knowledge itself described in the ontology (related to the service) but on the fact of using an ontology to represent such knowledge. A summary of the resources and defined operations is depicted in Table I. As mentioned in the description of the converter module, individuals are exchanged by using a developed structure designated as IndividualWS. Using OWL language, an individual of the ontology can be described as a member of a class with individual axioms or facts as individual property values (datatype and object properties).

HG AND TS MANAGEMENT MODULES:

Two management modules and web technology modules inside the HG and the TS constitute the main parts of the telemedicine system (see Fig. 1). The modules that comprise the architecture have been developed using .NET technologies. Specifically, the .NET framework (version 3.5) has been used to process the ontology and create new instances, data acquisition, and manipulation when the rules are applied. Regarding the web modules the components of the remote management module installed in the TS are depicted in Fig. 1. This management module includes the following three components:

1) Ontology knowledge base module: This module contains the ontology knowledge models and the instances of the registered management profiles. The TDB triple-store has been used to store the ontology model and new instances in this knowledge base module.

2) Converter module: The communication module of this architecture is mainly based on OWL instances exchanged generically by means of a developed object structure named IndividualWS. The converter module is used to wrap and unwrap the individuals structure used to exchange information with web clients. Furthermore, this module incorporates some reasoning tasks. Ontology-based reasoning is used in order to check instances before including new information

in the model and to ensure the consistency of the model.

3) Rules module: This module is used to store rules associated with each management profile. These rules are subsequently transferred by means of an XML file. As shown in Fig. 1, an additional GUI is required in order to make easier for EM, technical or clinical (physician), the process of defining the profiles and the rules. We are currentlyworking in the development of this GUI combining ontology visualization techniques and usability methods. The methodology used to design this interface components of the management module installed in the HG are equally depicted in Fig. 1. This last management module has been designated the “Semantic Autonomic Agent.” This module plays a key role in the architecture. It is in charge of integrating incoming data and executing the management tasks described in the management profile.

The communication between this agent and the management module installed at the remote site is established through a web client connection to the WS installed in the remote TS. The architecture of the agent comprises the ontology knowledge base module, the rules module, the converter module, and the following modules.

1) MAPE module: This module constitutes the computing core of the agent. It will be used to run the tasks specified in each management profile, hence to execute the closed loop from the MAPE loop process.

2) Integrator module: Information transferred by MDs and also contextual data provided by patients will be acquired in this module, which integrates data coming from different data sources.

3) Reminders and alarms module: This module includes clock functionalities to ask patients about data (reminders) or to collect information from a specific software resource.

4) Actions module: This last module is used to execute actions described within the execution tasks of the management profile if an abnormal finding occurs.

FLOW AND WORKFLOW PERFORMANCE:

All the modules and sources involved in the management procedure. The first step (see Fig. 3) consists in the download of the management profile (patient profile or technical profile). First of all, an instance of the management profile should be configured by an EM placed at a remote site. Furthermore, a set of individual rules should be configured for each particular management purpose. As shown in Fig. 3, the designed GUI helps the physician with the ontology instantiation process and the rules definition. The outputs of this interface (which uses selected classes of the ontology as a navigation tool) are a personalized management profile and a set of rules gathered in an XML file. Other functionalities such as queries over acquired data or crossing data among patients to take some decisions could be of interest to be included in this tool.

The communication is always initiated by the user (web client at HG). Through a connection to the web service, the user (the patient in the telemonitoring scenario) situated at home site will acquire the required management profile. As shown in Fig. 3, if the user requests for an update of his/her management profile, then the version of the available profile at the TS will be requested for its evaluation (GET property value). When the user requests a new management profile, first, it is checked whether the ontology to download it is available (GET ontology). After that, the rules and the management profile will be downloaded when required.

The methods involved are 1) GET (rules) and 2) GET (individual). Note that the TLS authentication phase is not depicted in Fig. 3, but it is initially carried out in order to allow the web client connection to the web service. As depicted in Fig. 3, the associated management profile is extracted from the ontology and the instances of the ontology managed by Jena are wrapped into the IndividualWS structure through the converter module. Once the management profile is in the HG, it will be processed into the converter module, unwrapped, and inserted as individuals managed by Jena in the ontology. Once the management profile has been included in the ontology knowledge base module of the HG, it will be evaluated in the MAPE module and the management procedure will be performed by running the tasks specified in the profile.

CHAPTER 5

5.0 SYSTEM STUDY:

5.1 FEASIBILITY STUDY:

Three key considerations involved in the feasibility analysis are

ECONOMICAL FEASIBILITY
TECHNICAL FEASIBILITY
SOCIAL FEASIBILITY

5.1.1 ECONOMICAL FEASIBILITY:

5.1.2 TECHNICAL FEASIBILITY

5.1.3 SOCIAL FEASIBILITY:

5.2 SYSTEM TESTING:

5.2.1 UNIT TESTING:

Description	Expected result
Test for application window properties.	All the properties of the windows are to be properly aligned and displayed.
Test for mouse operations.	All the mouse operations like click, drag, etc. must perform the necessary operations without any exceptions.

5.1.2 FUNCTIONAL TESTING:

Description	Expected result
Test for all modules.	All peers should communicate in the group.
Test for various peer in a distributed network framework as it display all users available in the group.	The result after execution should give the accurate result.

5.1. 3 NON-FUNCTIONAL TESTING:

Load testing
Performance testing
Usability testing
Reliability testing
Security testing

5.1.4 LOAD TESTING:

Description	Expected result
It is necessary to ascertain that the application behaves correctly under loads when ‘Server busy’ response is received.	Should designate another active node as a Server.

5.1.5 PERFORMANCE TESTING:

Description	Expected result
This is required to assure that an application perforce adequately, having the capability to handle many peers, delivering its results in expected time and using an acceptable level of resource and it is an aspect of operational management.	Should handle large input values, and produce accurate result in a expected time.

5.1.6 RELIABILITY TESTING:

Description	Expected result
This is to check that the server is rugged and reliable and can handle the failure of any of the components involved in provide the application.	In case of failure of the server an alternate server should take over the job.

5.1.7 SECURITY TESTING:

Description	Expected result
Checking that the user identification is authenticated.	In case failure it should not be connected in the framework.
Check whether group keys in a tree are shared by all peers.	The peers should know group key in the same group.

5.1.8 WHITE BOX TESTING:

Description	Expected result
Exercise all logical decisions on their true and false sides.	All the logical decisions must be valid.
Execute all loops at their boundaries and within their operational bounds.	All the loops must be finite.
Exercise internal data structures to ensure their validity.	All the data structures must be valid.

5.1.9 BLACK BOX TESTING:

Description	Expected result
To check for incorrect or missing functions.	All the functions must be valid.
To check for interface errors.	The entire interface must function normally.
To check for errors in a data structures or external data base access.	The database updation and retrieval must be done.
To check for initialization and termination errors.	All the functions and data structures must be initialized properly and terminated normally.

All the above system testing strategies are carried out in as the development, documentation and institutionalization of the proposed goals and related policies is essential.

CHAPTER 6

6.0 SOFTWARE DESCRIPTION:

6.1 JAVA TECHNOLOGY:

Java technology is both a programming language and a platform.

The Java Programming Language

The Java programming language is a high-level language that can be characterized by all of the following buzzwords:

Simple
- Architecture neutral
- Object oriented
- Portable
- Distributed
- High performance
- Interpreted
- Multithreaded
- Robust
- Dynamic
- Secure

6.2 THE JAVA PLATFORM:

The Java platform has two components:

The Java Virtual Machine (Java VM)
The Java Application Programming Interface (Java API)

You’ve already been introduced to the Java VM. It’s the base for the Java platform and is ported onto various hardware-based platforms.

The following figure depicts a program that’s running on the Java platform. As the figure shows, the Java API and the virtual machine insulate the program from the hardware.

6.3 WHAT CAN JAVA TECHNOLOGY DO?

The essentials: Objects, strings, threads, numbers, input and output, data structures, system properties, date and time, and so on.
Applets: The set of conventions used by applets.
Networking: URLs, TCP (Transmission Control Protocol), UDP (User Data gram Protocol) sockets, and IP (Internet Protocol) addresses.
Internationalization: Help for writing programs that can be localized for users worldwide. Programs can automatically adapt to specific locales and be displayed in the appropriate language.
Security: Both low level and high level, including electronic signatures, public and private key management, access control, and certificates.
Software components: Known as JavaBeans^TM, can plug into existing component architectures.
Object serialization: Allows lightweight persistence and communication via Remote Method Invocation (RMI).
Java Database Connectivity (JDBC^TM): Provides uniform access to a wide range of relational databases.

The Java platform also has APIs for 2D and 3D graphics, accessibility, servers, collaboration, telephony, speech, animation, and more. The following figure depicts what is included in the Java 2 SDK.

6.4 HOW WILL JAVA TECHNOLOGY CHANGE MY LIFE?

Get started quickly: Although the Java programming language is a powerful object-oriented language, it’s easy to learn, especially for programmers already familiar with C or C++.
Write less code: Comparisons of program metrics (class counts, method counts, and so on) suggest that a program written in the Java programming language can be four times smaller than the same program in C++.
Write better code: The Java programming language encourages good coding practices, and its garbage collection helps you avoid memory leaks. Its object orientation, its JavaBeans component architecture, and its wide-ranging, easily extendible API let you reuse other people’s tested code and introduce fewer bugs.
Develop programs more quickly: Your development time may be as much as twice as fast versus writing the same program in C++. Why? You write fewer lines of code and it is a simpler programming language than C++.
Avoid platform dependencies with 100% Pure Java: You can keep your program portable by avoiding the use of libraries written in other languages. The 100% Pure Java^TMProduct Certification Program has a repository of historical process manuals, white papers, brochures, and similar materials online.
Write once, run anywhere: Because 100% Pure Java programs are compiled into machine-independent byte codes, they run consistently on any Java platform.
Distribute software more easily: You can upgrade applets easily from a central server. Applets take advantage of the feature of allowing new classes to be loaded “on the fly,” without recompiling the entire program.

6.5 ODBC:

6.6 JDBC:

JDBC was announced in March of 1996. It was released for a 90 day public review that ended June 8, 1996. Because of user input, the final JDBC v1.0 specification was released soon after.

6.7 JDBC Goals:

The goals that were set for JDBC are important. They will give you some insight as to why certain classes and functionalities behave the way they do. The eight design goals for JDBC are as follows:

SQL Level API

SQL Conformance

JDBC must be implemental on top of common database interfaces

Provide a Java interface that is consistent with the rest of the Java system

Because of Java’s acceptance in the user community thus far, the designers feel that they should not stray from the current design of the core Java system.

Keep it simple

Use strong, static typing wherever possible

Strong typing allows for more error checking to be done at compile time; also, less error appear at runtime.

Keep the common cases simple

Finally we decided to precede the implementation using Java Networking.

And for dynamically updating the cache table we go for MS Access database.

Java ha two things: a programming language and a platform.

Java is a high-level programming language that is all of the following

Simple Architecture-neutral

Object-oriented Portable

Distributed High-performance

Interpreted Multithreaded

Robust Dynamic Secure

Compilation happens just once; interpretation occurs each time the program is executed. The figure illustrates how this works.

6.7 NETWORKING TCP/IP STACK:

The TCP/IP stack is shorter than the OSI one:

TCP is a connection-oriented protocol; UDP (User Datagram Protocol) is a connectionless protocol.

IP datagram’s:

UDP:

UDP is also connectionless and unreliable. What it adds to IP is a checksum for the contents of the datagram and port numbers. These are used to give a client/server model – see later.

TCP:

TCP supplies logic to give a reliable connection-oriented protocol above IP. It provides a virtual circuit that two processes can use to communicate.

Internet addresses

In order to use a service, you must be able to find it. The Internet uses an address scheme for machines so that they can be located. The address is a 32 bit integer which gives the IP address.

Network address:

Class A uses 8 bits for the network address with 24 bits left over for other addressing. Class B uses 16 bit network addressing. Class C uses 24 bit network addressing and class D uses all 32.

Subnet address:

Internally, the UNIX network is divided into sub networks. Building 11 is currently on one sub network and uses 10-bit addressing, allowing 1024 different hosts.

Host address:

8 bits are finally used for host addresses within our subnet. This places a limit of 256 machines that can be on the subnet.

Total address:

The 32 bit address is usually written as 4 integers separated by dots.

Port addresses

Sockets:

#include <sys/types.h>

#include <sys/socket.h>

int socket(int family, int type, int protocol);

6.8 JFREE CHART:

JFreeChart is a free 100% Java chart library that makes it easy for developers to display professional quality charts in their applications. JFreeChart’s extensive feature set includes:

A consistent and well-documented API, supporting a wide range of chart types;

A flexible design that is easy to extend, and targets both server-side and client-side applications;

Support for many output types, including Swing components, image files (including PNG and JPEG), and vector graphics file formats (including PDF, EPS and SVG);

JFreeChart is “open source” or, more specifically, free software. It is distributed under the terms of the GNU Lesser General Public Licence (LGPL), which permits use in proprietary applications.

6.8.1. Map Visualizations:

6.8.2. Time Series Chart Interactivity

6.8.3. Dashboards

6.8.4. Property Editors

CHAPTER 7

APPENDIX

7.1 SAMPLE SOURCE CODE

7.2 SAMPLE OUTPUT

CHAPTER 8

8.1 CONCLUSION:

This study describes architecture to enable data integration and its management in an ontology-driven telemonitoring solution implemented in home-based scenarios. This is an innovative architecture that facilitates the integration of several management services at home sites using the same software engine. The architecture has been specifically studied to support both technical and clinical services in the telemonitoring scenario, thus avoiding installing additional software for technical purposes.

HOTMES ontology used at the conceptual layer to describe a management profile on the one hand, our ontology contributes to integrate data and its management offering benefits in terms of knowledge representation, workflow organization, and self-management capabilities to the system. Its combination with rules allows providing personalized services.

This application ontology could be in future improved by introducing concepts from domain ontology. On the other hand, the data and communication layer of the architecture, based on the REST WS, was oriented to minimizing the consumption of resources and providing reusable key ideas for future ontology-based architecture developments.

8.2 FUTURE ENHANCEMENT

This solution represents a further step toward the possibility of establishing more effective home-based telemonitoring systems and thus improving the remote care of patientswith chronic diseases. As it was reported in, good telemedicine implementations are developed after a process where the dynamic interaction among a combination of socio-technical and also clinical factors is optimized. It means that additional work should be done (e.g., to measure the interaction of the

patient–doctor using the system and also the truthfulness of the system for a long period of time) before adopting this solution in a real scenario its complete development, first, a concordance study should be conducted in order to determine its clinical efficiency. Then, a social impact study should be conducted in order to determine how the system allowed improving patient’s quality of life. Regarding these last studies, the results presented in evidence the benefits of telemonitoring systems while linking their success to the usability design issues and features.

CHAPTER 9

9.1 REFERENCES

[1] I. Martinez et al., “Seamless integration of ISO/IEEE11073 personal health devices and ISO/EN13606 electronic health records into an endto- end interoperable solution,” Telemed. J. E. Health, vol. 16, no. 10, pp. 993–1004, 2010.

[2] M. Figueredo and J. Dias, “Service oriented architecture to support realtime implementation of artifact detection in critical care monitoring,” in Proc. IEEE. Annu. Int. Conf. Eng. Med. Biol. Soc., 2011, pp. 4925–4928.

[3] JD. Trigo, I. Mart´ınez, A. Alesanco, A. Kollmann, J. Escayola, D. Hayn, G. Schreier, and J. Garc´ıa, “An integrated healthcare information system for end-to-end standardized exchange and homogeneous management of digital ECG formats,” IEEE Trans. Inf. Technol. Biomed., vol. 16, no. 4, pp. 518–529, Jul. 2012.

[4] F. Paganelli and D. Giuli, “An ontology-based system for context-aware and configurable services to support home-based continuous care,” IEEE Trans. Inform. Tech. Biomed., vol. 15, no. 2, pp. 324–333, 2011.

[5] D. Ria˜no, F. Real, J. A. L´opez-Vallverd´u, F. Campana, S. Ercolani, P. Mecocci, R. Annicchiarico, and C. Caltagirone, “An ontology-based personalization of health-care knowledge to support clinical decisions for chronically ill patients,” J. Biomed. Informat., vol. 45, no. 3, pp. 429–446, 2012.

[6] I. Berges, J. Bermudez, and A. Illarramendi, “Towards semantic interoperability of electronic health records,” IEEE Trans. Inf. Technol. Biomed., vol. 16, no. 3, pp. 424–431, May 2012.

[7] G. Mulligan and D. Gracanin, “A comparison of SOAP and REST implementations of a service based interaction independence middleware framework,” in Proc. Winter Simul. Conf., 2009, pp. 1423–1432.

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