Shuffled Complex Evolution Approach for Load Balancing of Gateways in Wireless Sensor Networks

Abstract

Energy consumption is one of the important factor of Wireless Sensor Networks (WSN). It has much attention in many fields. From recent studies, it is observed that energy consumption in WSN is challenging task as the energy is limited resource. This energy is needed for sensor nodes operation. In order to maximize the network lifetime, energy consumption should be mitigated. In cluster based WSN, cluster head i.e., the leader of cluster performs various activities, such as data collection from its member nodes, data aggregation and data exchange with base station. Hence, load balancing in WSNs is one of the challenging task to maximize network lifetime. In order to address this problem, in this paper, Shuffled Complex Evolution (SCE) algorithm is used. A novel fitness function is also designed to evaluate fitness of solutions produced by SCE algorithm. In SCE, the solutions with best and worst fitness value exchange their information to produce new off-spring. We have simulated proposed load balancing algorithm along with other state-of-the-art load balancing algorithms, namely Node Local Density Load Balancing, Score Based Load Balancing, Simple Genetic Algorithm based load balancing, Novel Genetic Algorithm based Load Balancing. It is observed from experimental results that proposed load balancing algorithm outperforms state-of-the-art load balancing algorithms in terms of load balancing, energy consumption, execution time, number of sensor nodes and number of heavy loaded sensor nodes.