Analysis Of The Characteristics Of M2M Traffic

The characteristics of network traffic vary with the development of network, which goes from early short-range correlations, Markov property to the current self-similarity, long-range correlations, etc. With the development of the Internet of Things (IOT), tremendous amounts of Machine-to-Machine (M2M) devices will be added to the network, which will have great impact on network. Next generation network (NGN) with the feature of communication between things is completely different from the current ones based on users. As fundamental changes have taken place in network traffic, it poses new challenges to the planning, design, performance evaluation and quality of service for network.Firstly, the development of network traffic characteristics and the system structure of IOT are analyzed in the thesis. Self-similarity--one of network characteristics as well as the research methods of self-similarity are introduced. In addition, the characteristics of several typical M2M applications are analyzed acquiring different traffic models of different applications. Then, simulations through MATLAB are done to produce the traffic of different devices scale, and the self-similarity of traffic is analyzed. The results indicate that self-similarity varies from traffic to traffic, which is, some traffic has self-similarity while others don’t, and some may be strong and others may be weak. Meanwhile, with the increase of terminal scale, the changing rules of the self-similarity are also different, some are enhanced and some are stable, while others may be weakened. Furthermore, traffic aggregations between different M2M as well as actual collected M2M and Internet are simulated. Next, traffic aggregations characteristics are analyzed, and it turns out that it does have some resemblance between the changing rules of traffic aggregations characteristics and those of M2M traffic self-similarity. Meanwhile, the results confirms that the variance of flow source has a significant impact on the flow of traffic aggregation characteristics. Finally, characteristics of actual collection for sensor network traffic are analyzed, and confirm the analysis above.In conclusion, through the analysis of characteristics of M2M traffic and the characteristics of traffic aggregation, it is found that traffic aggregation would show different self-similarity for different M2M. Therefore, it can be predicted that the self-similarity of the next generation of network traffic will be much uncertain.