Particle Swarm Optimization based Energy analysis in WSN

minimize the overall energy consumption in a Wireless Sensor Network

The objective of this program is to apply Particle Swarm Optimization (PSO) to minimize the overall energy consumption in a Wireless Sensor Network by optimally selecting the cluster head position. Since sensor nodes are battery powered, reducing transmission distance is critical for extending network lifetime. The proposed PSO-based approach models each particle as a potential cluster head location and evaluates its fitness based on the total transmission energy consumed by sensor nodes and the cluster head while communicating with the base station. The findings show that PSO efficiently converges to an optimal or near-optimal cluster head position that significantly reduces energy consumption compared to random selection. This demonstrates that swarm intelligence techniques such as PSO are well suited for energy-efficient clustering in wireless sensor networks and can effectively enhance network performance and lifetime.