Congestion Control Technology For Wireless Sensor Network

In recent years, with the rapid development of electronic, wireless communication and sensor technology et al, wireless sensor network has been developed great. In WSN, the many-to-one communication mode and the memory restrained characteristic of node, make network more vulnerable to congestion. Congestion of WSN can cause lower energy efficiency, Qos problem, et al. Consequently, congestion problem for WSN is urgent to be solved.In this thesis, for the congestion problem of wireless sensor networks, we have studied the features of it, and combined with the charcteristics of wireless sensors networks to find the method of relieve congestion. Then we put forward some new methods and improvement to relieve congestion. Simulation has demonstrated its availability. The main contribution includes:(1) In wireless sensor networks, when congestion occurs, the bandwidth allocation between nodes that away from different transmission distances would loss fairness. In order to deal with the above problem, we propose congestion control mechanism concerning fairness. Firsty, the mechanism introduces QPSO algorithm into PID Queue Management to avoid the node’s buffer overflow. Secondly, it combines the network congestion status and packet transmission distance to dynamically manage the queue.(2) A congestion control mechanism which combines compress sensing and rate control is proposed to solve the congestion problem of WSNs. For local congestion, the sending rate of the upstream node will be adjusted by using open-loop hop-by-hop back-pressing mechanism. For global congestion, compressive sensing technology will be utilized to reduce redundancy information, thus relieving network congestion. To guarantee the authenticity of information, networks collects information in normal mode after the congestion relieved.(3) For the problems of compressed sensing can’t adapt to the complex environment of Wireless Sensor Networks, a new congestion control algorithm based on fuzzy compressed sensing is proposed, which combines the congestion degree of network to dynamic adjust the dimension of observation matrix, thus make the compress sensing better adapt the complex environment of Wireless sensing networks. NS2simulation shows that the mechanism achieves better improvement to the congestion of wireless sensing network.Finally, a comprehensive overview of the dissertation be summarized and the future research directions are also discussed.