Optimized sink node path using particle swarm optimization

A wireless sensor network (WSN) is comprised of large number of sensors distributed in a monitoring field and a sink node to gather process and control data. The performance of the network depends on the behavior of the sink node and its location. An optimized sink node path will be efficient and economical for operation of the network. In this paper, we propose a novel method to derive the optimum path of a sink node in a fixed network of sensor nodes considering practical difficulties such as the limitation in the sink movement. The proposed evolutionary computing technique based simulator PSO-SIMSENS is an integrated system of particle swarm optimization and a sensor network simulator with an appropriate fitness function. This system can be configured for numerous applications such as manufacturing, bush fire monitoring etc. The simulation results show that our approach achieves efficient performance of WSN with maximum field coverage while sink node is mobile.