Congestion control for self similar traffic in wireless sensor network

Abstract

Wireless sensor networks (WSNs) have inspired many research domains in recent years. Congestion is a major issue faced by such networks, which causes heavy loss in data transmissions. Congestion is caused due to several reasons, such as heavy traffic, link failure, node failure and many more. There are various techniques developed for combatting network congestion. In this paper, we have proposed a technique for prediction of the congestion before it happens and controlling the situation before it becomes worse. Congestion in the network is controlled by adjusting the traffic rate of sources. Source nodes change their transmission rate as soon as they receive the control signal. Our algorithm is developed especially for managing congestive situations created by self similar traffic. The self-similarty in network traffic is simulated Pareto distribution. Congestion in the network is detected by analyzing the buffer ratio of nodes. Further, the simulation results show that our algorithm outperforms other existing techniques in terms of packet delivery ratio and average number of packets dropped.