An Efficient Cluster Head Selection Algorithm for Wireless Sensor Networks Using Fuzzy Inference Systems

Abstract

An efficient cluster head selection algorithm in wireless sensor networks is proposed in this paper. The implementation of the proposed algorithm can improve energy which allows the structured representation of a network topology. According to the residual energy, number of the neighbors, and the centrality of each node, the algorithm uses Fuzzy Inference Systems to select cluster head. The algorithm not only balances the energy load of all nodes, but also provides a reliable selection of a new cluster head and optimality routing for the whole networks. Simulation results demonstrate that the proposed algorithm effectively increases the accuracy to select a cluster head and prolongs the network lifetime