An IPO-Based Clustering Algorithm for improving Lifetime in Wireless Sensor Networks

Clustering in wireless sensor networks (WSNs) is the process of dividing the nodes of the WSN into groups to reduce energy consumption. However, CH selection in WSN is an NP-hard optimization problem that can’t be solved effectively by traditional methods. In this paper, we propose a cluster head selection scheme based on Inclined Planes system Optimization (IPO) to balance the energy consumption among different sensors nodes. In IPO algorithm, the problem space is searched by small balls (agents of the algorithm) to find optimal solutions which are function of the position and height of balls using a fitness function. The proposed clustering algorithm is compared with algorithms based on LEACH, genetic algorithm, particle swarm optimization and K-means. The simulation results using MATLAB demonstrate that the proposed algorithm provides better performance metrics such as network lifetime and data received by BS compared with existing techniques.