An Energy Efficient Scalable Clustering Protocol for Dynamic Wireless Sensor Networks

Abstract

The issue of energy constraint has always been a challenging task in the research field of wireless sensor networks. Clustering is the most effective approach for enhancing the performance of wireless sensor networks to a great extent in terms of energy consumption, network lifetime and throughput. However, the uneven formation of clusters can lead to faster energy depletion of few nodes, and thus results in premature failure of the wireless sensor network. This paper proposes an energy-efficient scalable clustering protocol (EESCP) which considers inter-cluster and intra-cluster distances to generate balanced clusters. A novel Dragonfly algorithm based particle swarm optimization technique is proposed to optimize the selection of cluster heads. Further, extensive simulations have been carried out by varying node densities and network sizes to demonstrate the full potential of EESCP.