I‐FBECS: Improved fuzzy based energy efficient clustering using biogeography based optimization in wireless sensor network

Abstract

AbstractCluster formation and optimal cluster head selection are two optimization problems in wireless sensor network (WSN) for prolonged lifetime. To address the above mentioned issue, biogeography based selection of cluster heads along with efficient cluster formation is propound in this article which improves the performance of fuzzy based enhanced clustering scheme (FBECS). A novel fitness function is formulated by making use of remnant energy, distance to base station (BS), and density around node for optimal cluster head selection using biogeography based optimization (BBO). A rank based mechanism is developed for non‐cluster head nodes for selecting their cluster head. Routing technique for region based forwarding is designed to improve the lifetime expectancy. The proposed I‐FBECS is compared with two state of the art protocols namely LEACH and FBECS. Simulation results reveal an improved stability period by 33.8% and 38.9% over FBECS and LEACH, respectively. The proposed I‐FBECS exhibits better load balancing and improvement in terms of more alive nodes per round, more packets forwarded to the BS, improved average remnant energy, and extended lifetime. The proposed I‐FBECS is suitable for applications where the BS is located at a distant place.