An Optimum Clustered Grid-Based Particle Swarm Optimization to Enhance Efficiency Energy in Wireless Sensor Networks

Abstract

Wireless sensor nodes are small but heavy-duty devices. This small device is tasked with monitoring and measuring environmental conditions with limited resources. The main problem is the limited battery capacity. While changing batteries or recharging is not possible routinely. Clustering is a technique that can be utilized to overcome problems in wireless sensor networks effectively. However, to set the optimal amount of clusters and to select the optimal cluster heads (CH) are non-deterministic polynomial-time hard (NP-hard) problem. Optimum Clustered Grid-Based (OCGB) protocol proposed in order to enhance energy efficiency and to protract the working time of sensor nodes. At the beginning operating time, OCGB splits network area into grids. At the next step, OCGB set the optimal amount of clusters in every grid. Furthermore, the OCGB utilizes the Particle swarm optimization (PSO) for forming clusters and selecting the optimal CHs. Evaluation is performed with MATLAB and compared with other protocols, namely LEACH. Simulation results present that our proposed protocol OCGB has better performance in terms of energy efficiency and network lifetime compared to LEACH protocol.