Modified Particle Swarm Optimization for Hybrid Wireless Sensor Networks Coverage

Abstract

Efficient network coverage and connectivity are the requisites for most Wireless Sensor Network deployments, particularly those concerned with area monitoring. The Coverage Control Technology is one of the basic technologies of wireless sensor network, and is mainly concerned about how to prolong the network lifetime on the basis of meeting users’ perception demand. To optimize wireless sensor networks coverage, an algorithm which is based on particle swarm optimization with dynamic clonal selection is proposed. This algorithm controls the clonal quantity and variation range of particle which represents the locations of all mobile sensor nodes, by coverage rate and similarity among the swarm to avoiding being trapped in local optimum. By comparison of the simulation results with other algorithms, this optimization algorithm could improve the performance of network coverage more effectively.