Energy EC: An artificial bee colony optimization based energy efficient cluster leader selection for wireless sensor networks

Abstract

In recent times, the applications of cluster-based Wireless Sensor Networks (WSNs) have shown rapid growth. Many researchers are working on approaches for an efficient way of cluster formation and selecting a cluster leader in a way to improve the energy efficiency of the WSN. One of the biggest challenges for the selection of a suitable cluster leader is that which criteria should be given priority over others. This paper consists of such an approach that deals with the cluster leader selection in the cluster based on the fitness function. At first, the cluster of sensor nodes is created using the k-means clustering algorithm and then the optimization of the fitness function is done with nature-inspired optimization technique is known as Artificial Bees Colony (ABC) optimization. The objective function considered for the optimization is based on; sensor’s energy; sink distance from cluster leader; and the cluster members distance. The benefit of the chosen objective function is that it yields the optimal cluster leaders. After simulating it is observed that the results obtained are better than that of other similar works.