Particle Swarm Optimization Algorithm for Energy-Efficient Cluster-Based Sensor Networks

Abstract

In order to reduce the traffic load and improve the system's lifetime, a cluster-based routing protocol has attracted more attention. In cluster-based sensor networks, energy can be conserved by combining redundant data from nearby sensors into cluster head nodes before forwarding the data to the destination. The lifespan of the whole network can also be expanded by the clustering of sensor nodes and through data aggregation. In this paper, we propose a cluster-based routing protocol which uses the location information of sensors to assist in network clustering. Our protocol partitions the entire network into several clusters by a particle swarm optimization (PSO) clustering algorithm. In each cluster, a cluster head is selected to deal with data aggregation or compression of nearby sensor nodes. For this clustering technique, the correct selection of the number of clusters is challenging and important. To cope with this issue, an energy dissipation model is used in our protocol to automatically estimate the optimal number of clusters. Several variations of PSO-clustering algorithm are proposed to improve the performance of our protocol. Simulation results show that the performance of our protocol is better than other protocols.