Research On Congestion Control In Wireless Sensor Networks

Wireless sensor network is easy to occur congestion, this is because the nodes in WSN are deployed densely, the node’s storage capacity is limited and its multi-hop transmission property, and other reasons. Congestion will aggravate the wireless channel conflict and collision, and cause massive data packets loss, transmission latency increase, which affect the network performance seriously. The author studied a lot Chinese and English literature, and studied the existing congestion control algorithms deeply by summarizing and comparing. On the basis of analysis some representative congestion control algorithms, the main innovation of this article have the following two aspects:(1) It is unreasonable to try to reduce the source traffic into the network during congestion occurrence when important data packets are transmitted in WSN. This will reduce the fidelity of observed by applications and influence the performance of the network. Aiming at this issue, a congestion control algorithm based on multiple attribute decision making theory (CCAMA) was proposed. CCAMA considers the residual energy, congestion level, hop number from the original path and channel utilization of nodes as the basis for selecting next-hop, and selects the most appropriate next-hop by introducing Vikor multiple attribute decision making theory, so the distributary routing path is established to relieve congestion. Simulation results show that CCAMA can effectively improve the network capacity, ensure the real-time performance and prolong the network life cycle.(2) In order to address the congestion problem in WSN, the fourth chapter proposed a cross-layer congestion control algorithm based on traffic prediction. The algorithm creates a congestion prediction model, and it activates congestion mitigation mechanisms based on prediction result in advance. It adjusts node backoff time of MAC layer combined with the prediction result dynamically, so as to change the channel access priorities of the nodes within the congestion region; At the same time, it adjusts upstream node’s rate based on node’s degree number information. Experiment results show that the algorithm can reduce the packet loss number and improve the energy efficiency significantly.