Cloud based machine-to-machine (M2M) communications have emerged to achieve ubiquitous and autonomous data transportation for future daily life in the cyber-physical world. In light of the need of network characterizations, we analyze the connected M2M network in the machine swarm of geometric random graph topology, including degree distribution, network diameter, and average distance (i.e., hops). Without the need of end-to-end information to escape catastrophic complexity, information dissemination appears an effective way in machine swarm. To fully understand practical data transportation, G/G/1 queuing network model is exploited to obtain average end-to-end delay and maximum achievable system throughput.
Furthermore,
as real applications may require dependable networking performance across the
swarm, quality of service (QoS) along with large network diameter creates a new
intellectual challenge. We extend the concept of small-world network to form
shortcuts among data aggregators as infrastructure-swarm two-tier heterogeneous
network architecture, and then leverage the statistical concept of network control
instead of precise network optimization, to innovatively achieve QoS
guarantees. Simulation results further confirm the proposed heterogeneous
network architecture to effectively control delay guarantees in a statistical
way and to facilitate a new design paradigm in reliable M2M communications.
1.2 INTRODUCTION:
Cloud based machine-to-machine (M2M) communications have emerged to enable services through interaction between cyber and physical worlds, achieving ubiquitous and autonomous data transportation among objects and the surrounding environment in our daily lives. The wireless network involving tremendous machines that the availability of end-to-end information at each machine is not possible is referred to the large M2M network, which is getting importance into next-generation wireless systems. While these tremendous machines have short-range communication capabilities, multi-hop networking is a must for information dissemination over machine swarm. The connectivity and low delivery latency in the machine swarm are consequently crucial to achieve reliable communications.
However, lacking complete understanding of large network characteristics, effective traffic control for message delivery remains open a proper control scheme of routing with quality-of-service (QoS) guarantee regarding end-to-end delay becomes an urgent need to practically facilitate M2M communications. This is even more challenging due to the scalability of multi-hop ad hoc networks and energy-efficient and spectral efficient operation for each machine. To investigate the routing mechanism for large-scale networks, network topology analysis can be scientifically exploited by random network analysis provides a comprehensive study in network structure and functions from complex networks perspective. Aiming at social communities mediated by network technologies, reviews the historical research for community analysis and community discovery methods in social media.
We develop an unbiased sampling for users in an online social network by crawling the social graph, they further examine multiple underlying relations for such network in to introduce a random walk sampling. For social networks related research, proposes the information-centric networking as it brings the advantages to the network operator and the end users. Exploring various research challenges in context management, presents a context management architecture that is suitable for social networking systems enhanced with pervasive features. Through a survey of current routing solutions, discuss the trend toward social based routing protocols, which are classified by employed network graph.
In addition, to employ social network analysis in message delivery remarkably pioneers the methodology to exercise the small-world phenomenon of social networks in navigation, successfully creating transmissions with less delay. Small-world phenomenon plays a crucial role in social networks, which states that each individual in such network links to others by a short chain of acquaintances and has great potential for improving spectral and energy efficiency for shorting the end-to-end delay. Reference also presents a thorough examination of average message delivery time for small-world networks in the continuum limit. Via random network analysis, studies the properties of giant component in wireless multi-hop networks, while provides a heterogeneous structure for such networks and conducts the throughput and delay analysis. Furthermore, the concepts of rumor and gossip routing algorithms are also widely employed in sensor networks for disconnected delay-tolerant MANETs and generalized complex networks, and respectively provide the social network analysis for information flow and epidemic information dissemination.
In this paper, inspired by small-world
phenomenon, we connect data aggregators (DAs) to machine swarm and propose a promising
two-tier heterogeneous architecture with DA’s smallworld network for statistical traffic
control in large M2M communication networks. To address efficient dissemination
control for routing and QoS such as surveillance applications, we first
analytically supply the condition to establish connected M2M networks and
explore some essential geometric properties (i.e., degree distribution, network
diameter, and average distance) for the networks. Analytic bounds of average
distance characterize the average number of hops that machines’ packets need to
traverse over the swarm, thus dominating the QoS guarantee capability for
reliable communications. Furthermore, through G/G/1 (i.e., both inter-arrival
time and service time distributions of a traffic queue are arbitrary
distributions) queuing network model for traffic modeling, the practical data
transportation takes place in connected M2M networks. Both the average
end-to-end delay and maximum achievable throughput per machine from information
dissemination in machine swarm multi-hop networking are examined.
1.3 LITRATURE SURVEY
TOWARD UBIQUOTOUS MASSIVE ACCESS IN 3GPP MACHINE-TO-MACHINE COMMUNICATIONS IN 3GPP
AUTHOR: S. Lien, K. C. Chen, and Y. Lin,
PUBLISH: IEEE Commun. Mag., vol. 49, no. 4, pp. 66–74, Apr. 2011.
EXPLANATION:
To enable full
mechanical automation where each smart device can play multiple roles among
sensor, decision maker, and action executor, it is essential to construct
scrupulous connections among all devices. Machine-to-machine communications
thus emerge to achieve ubiquitous communications among all devices. With the
merit of providing higher-layer connections, scenarios of 3GPP have been
regarded as the promising solution facilitating M2M communications, which is
being standardized as an emphatic application to be supported by LTE-Advanced.
However, distinct features in M2M communications create diverse challenges from
those in human-to-human communications. To deeply understand M2M communications
in 3GPP, in this article, we provide an overview of the network architecture
and features of M2M communications in 3GPP, and identify potential issues on
the air interface, including physical layer transmissions, the random access
procedure, and radio resources allocation supporting the most critical QoS
provisioning. An effective solution is further proposed to provide QoS
guarantees to facilitate M2M applications with inviolable hard timing
constraints.
SMALL-WORLD NETWORKS EMPOWERED LARGE MACHINE-TO-MACHINE COMMUNICATIONS
AUTHOR: L. Gu, S. C. Lin, and K. C. Chen
PUBLISH: IEEE WCNC, 2013, pp. 1–6.
EXPLANATION:
Cloud-based
machine-to-machine communications emerge to facilitate services through linkage
between cyber and physical worlds. In addition to great challenges in a large
network of machine/sensor swarm, effective network architecture involving
interconnection of wireless infrastructure and multi-hop ad hoc networking in
the machine swarm remains open. Inspired by the small-world phenomenon in
social networks, we may establish a short-cut path under heterogeneous network
architecture through wireless infrastructure and cloud, by connecting to data
aggregators or access points in the machine swarm, such that end-to-end delay
can be significantly reduced. Our mathematical analysis on network diameter and
average delay, along with verifications by simulations, demonstrate spectral
and energy efficiency of our proposed heterogeneous network architecture in
large machine-to-machine communication networks.
COGNITIVE MACHINE-TO-MACHINE COMMUNICATIONS: VISIONS AND POTENTIALS FOR THE SMART GRID
AUTHOR: Y. Zhang et al.,
PUBLISH: IEEE Netw., vol. 26, no. 3, pp. 6–13, May/Jun. 2012.
EXPLANATION:
Visual capability
introduced to Wireless Sensor Networks (WSNs) render many novel applications
that would otherwise be infeasible. However, unlike legacy WSNs which are commercially
deployed in applications, visual sensor networks create additional research
problems that delay the real-world implementations. Conveying real-time video
streams over resource constrained sensor hardware remains to be a challenging
task. As a remedy, we propose a fairness-based approach to enhance the event
reporting and detection performance of the Video Surveillance Sensor Networks.
Instead of achieving fairness only for flows or for nodes as investigated in
the literature, we concentrate on the whole application requirement.
Accordingly, our Event-Based Fairness (EBF) scheme aims at fair resource
allocation for the application level messaging units called events. We identify
the crucial network-wide resources as the in-queue processing turn of the
frames and the channel access opportunities of the nodes. We show that fair
treatment of events, as opposed to regular flow of frames, results in enhanced
performance in terms of the number of frames reported per event and the
reporting latency. EBF is a robust mechanism that can be used as a stand-alone
or as a complementary method to other possible performance enhancement methods
for video sensor networks implemented at other communication layers.
CHAPTER 2
2.0 SYSTEM ANALYSIS
2.1 EXISTING SYSTEM:
Existing methods for nodes as investigated in the literature; machine-to-machine communications emerge to facilitate services through linkage between cyber and physical worlds. In addition to great challenges in a large network of machine/sensor swarm, effective network architecture involving interconnection of wireless infrastructure and multi-hop ad hoc networking in the machine swarm remains open. Inspired by the small-world phenomenon in social networks, we may establish a short-cut path under heterogeneous network.
Previous discussion of existing tradeoff, but heterogeneous schemes are able to provide promising guaranteed throughput even under strict QoS demand for tight τ.Moreover, Fig. 8 further provides the exhaustive throughput comparison among different scenarios to complete our evaluation. While QoS guaranteed throughput is upper bounded by maximum achievable throughput, the great throughput improvement is provided by heterogeneous architecture as compared with plain machine swarm.
QoS fair resource
allocation for the application level messaging units called events. We identify
the crucial network-wide resources as the in-queue processing turn of the
frames and the channel access opportunities of the nodes that fair treatment of
events, as opposed to regular flow of frames, results in enhanced performance
in terms of the number of frames reported per event and the reporting latency
can be used as a stand-alone or as a complementary method to other possible
performance enhancement methods for video sensor networks implemented at other
communication layers.
2.1.1 DISADVANTAGES:
2.2 PROPOSED SYSTEM:
Machine-to-machine (M2M) communications emerge to autonomously operate to link interactions between Internet cyber world and physical systems. We present the technological scenario of M2M communications consisting of wireless infrastructure to cloud, and machine swarm of tremendous devices. Related technologies toward practical realization are explored to complete fundamental understanding and engineering knowledge of this new communication and networking technology front. We connect data aggregators (DAs) to machine swarm and propose a promising two-tier heterogeneous architecture with DA’s smallworld network for statistical traffic control in large M2M communication networks address efficient dissemination control for routing and QoS such as surveillance applications.
We first analytically supply the condition to establish connected M2M networks and explore some essential geometric properties (i.e., degree distribution, network diameter, and average distance) for the networks. Analytic bounds of average distance characterize the average number of hops that machines’ packets need to traverse over the swarm, thus dominating the QoS guarantee capability for reliable communications. Furthermore, through G/G/1 (i.e., both inter-arrival time and service time distributions of a traffic queue are arbitrary distributions) queuing network model for traffic modeling, the practical data transportation takes place in connected M2M networks.
Aiming at statistical performance in
large M2M networks, we propose a statistical control mechanism for the networks
by establishing the heterogeneous network architecture and exploiting statistical
QoS guarantee for end-toend transmissions without the need of feedback control
at each link. By forming DA’s network with small-world property and linking
machines to DAs, this novel heterogeneous architecture significantly improves
the performance of end-to-end traffic for tolerable delay and makes dependable
communications possible from guaranteing traffic QoS, with extremely simple network
operation for each machine.
2.2.1 ADVANTAGES:
2.3.1 HARDWARE REQUIREMENT:
CHAPTER 3
3.0 SYSTEM DESIGN:
Data Flow Diagram / Use Case Diagram / Flow Diagram:
External sources or destinations, which may be people or organizations or other entities
Here the data referenced by a process is stored and retrieved.
People, procedures or devices that produce data’s in the physical component is not identified.
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:
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:
GEOMETRIC RANDOM GRAPH (GRG) :
M2M communication network consists of tremendous self organized machines/sensors and enables autonomous connections among different applications for ubiquitous communications upon such large swarm system. To facilitate this scenario into practice, providing the connectivity accompanied with reliable transportation is a must for such large network. In the following, we highlight the relevant research and introduce the M2M network model using geometric random graph (GRG) as its topology and local clustering property are suitable for benchmarking large wireless ad hoc sensor networks.
Without the need of end-to-end
information to escape catastrophic complexity, information dissemination
becomes the only way in machine swarm. We exploit an open G/G/1 queuing
network model for delay and throughput analysis of M2M networks. Furthermore,
the diffusion approximation is used to analyze the queuing network. Our analytical
methodology to deal with wireless networks have general inter-arrival and
service time distributions by providing closed form expressions of end-to-end
delay and maximum achievable throughput per node. In the following, to fully
understand practical data transportation, we present the traffic model and an
equivalent queuing network model in connected M2M networks.
4.1 ALGORITHM
M2M ROUTING ALGORITHM:
M2M routing algorithm, this paper studies the asymptotic performance of several statistical QoS requirements, such as end-to-end delay and maximum throughput as well as the throughput under guaranteed delay, for a general forwarding scheme inM2M network. What is more important, our previous work focuses on obtaining the traffic performance under a specific scenario setting, which can simplify the analysis, while failing to maintain the same level of transmission qualities when the scenario changes, e.g., the network topology or traffic pattern becomes different.
Proposed algorithms solve this challenge
through statistical dissemination control by leveraging the heterogeneous
network architecture. In particular, the upper layer of DAs’ network enables
shortcut transmissions to reduce the excess end-to-end delay from the long
route transmissions in the lower layer of machine swarm. A comprehensive
performance analysis upon such a heterogeneous architecture is also included in
this paper. With these accomplishments, we provide an original and significant
paradigm to facilitate M2M communications, practically realizing information
dissemination control to meet the need of time sensitive applications in next-generation
wireless standards.
4.2 MODULES:
NETWORK TOPOLOGY DESIGN:
SERVER CLIENT MODULE:
STATISTICAL QOS GUARANTEE:
M2M COMMUNICATION CONTROL:
END-TO-END DELAY ANALYSIS:
4.3 MODULE DESCRIPTION:
NETWORK TOPOLOGY DESIGN:
This module is developed to wireless mesh based Topology design all node place particular distance. Without using any cables then fully wireless equipment based transmission and received packet data. Node and wireless sensor between calculate distance and transmission range then physically all nodes interconnected. The sink is at the center of the circular sensing area.
This module is developed to node creation and more than 20 nodes placed particular distance. Wireless sensor placed intermediate area. Each node knows its location relative to the sink. Each node is programmed with the total number of nodes in the network.
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.
STATISTICAL QOS GUARANTEE:
M2M COMMUNICATION CONTROL:
M2M communication with low data rate and energy cost, the machine-to-DA communication with medium data rate, and the DA-to-DA communication with high data rate. We adopt the related values from as shown in Table II and set up the experiment as follows. The 1 Mb data is sent from the source machine to the destination machine in both plain machine swarm and heterogeneous architecture separately. Moreover, DAs’ communication capabilities are characterized as the number of machines z that can be served simultaneously by each single DA.
DAs for heterogeneous architecture with respect to the number of machines in the DA’s capability linearly increases, the required number of DAs drops exponentially. It suggests that few powerful DAs are preferable than bunch of DAs with limited capability. Furthermore, Fig. 10 shows the average end-to-end delay with respect to different area sizes of Metropolis. As the area size increases (so does the number of machines in each block), the heterogeneous architecture supports much less traffic delay than the plain machine swarm.
For example, with the area size 60 km2
and 108 machines, the delay from heterogeneous architecture is 115 s as
compared to 2,500 s from the swarm. Moreover, the linear curves in the log
scale of Fig. 10(b) confirms our asymptotic results, and suggest that the heterogeneous architecture outperforms the
plain machine swarm with about 95% delay reduction for 10 billion machines. To conclude,
by efficiently connecting few DAs to construct small world shortcuts, proposed
statistical control accompanied with heterogeneous architecture resolves the
undependable end-to end transmissions.
END-TO-END DELAY ANALYSIS:
We compare the performance of the proposed heterogeneous network architecture with plain machine swarm. Simulation results confirm that heterogeneous architecture achieves remarkable delay reduction as well as high throughput gain with only few DAs installed, favored by practical implementation in large M2M networks. All simulation parameters and value settings are listed in Table I. In particular, to ensure every packet could be sent to its corresponding destination from the source, a connected M2M network is first established via the proposed analysis (i.e., selecting the appropriate machine communication range r with respect to the total machine number n). When a source machine generates a packet, it routes the packet to a specific destination, uniformly selected among other machines.
Moreover, for plain machine swarm, source simply hops forward based on the sensing and relaying; for heterogeneous architecture, it employs dissemination without selecting a particular DA. In the following, we first evaluate average distance to DAs and end-to-end distance for plain machine swarm and heterogeneous architecture. Next, end-toend packet delay, maximum system throughput, and throughput under guaranteed delay are thoroughly examined for such different architecture and compared with simulation validation in the Metropolis is established to facilitate our design into an even more practical stage.
CHAPTER 8
8.1 CONCLUSION AND FUTURE WORK:
In this paper, we resolve the most critical challenge on providing statistical control for reliable information dissemination over large M2M communication networks. Examining network topology of M2M networks, the geometric properties of such large networks are well studied to analytically characterize message delivery over connected M2M networks.
Moreover, by leveraging queuing network model, the practical data transportation is employed and both the average end-to end delay and maximum achievable throughput for these connected networks are accessible. Based on above explorations, the promising statistical control with sophisticated small-world network of data aggregators and thus the heterogeneous architecture are proposed to establish shortcut paths among machine communications.
Performance evaluation verifies that
instead of exploiting long concatenation of multi-hop transmissions in the
machine swarm, our heterogeneous network architecture enables machines to
communicate through overlaid ultra-fast “highway”, like shortcut in small-world
networks, with desired throughput. It is particularly crucial for
next-generation networks of tremendous amounts of machines. Therefore, we successfully
achieve reliable communications via our proposed methodology and facilitate
novel traffic control in M2M communication networks.