An Energy-Efficient Multi-swarm Optimization in Wireless Sensor Networks

Wireless Sensor Networks are a group of sensors with inadequate power sources that installed in particular region to gather information from the surroundings. Designing energy-efficient data gathering methods large-scale (WSN) is one most difficult areas study. As every sensor node has finite amount energy. Battery significant source WSN. Clustering well-known technique for enhancing feature In proposed method multi-Swarm optimization based on Genetic Algorithm and Adaptive Hierarchical clustering-based routing protocol used network’s lifespan optimization. By using distributed transmission modification, an adaptive hierarchical algorithm consumption presented ensure continuous coverage entire area. To begin, terms balancing energy consumption. The Multi-Swarm (MSO) Algorithms select efficient Cluster Head (CH). It also improves longevity optimizes routing. result study’s findings, MSO-Genetic Hill climbing (GAHC) effective, as it increases number clusters created, average expended, computation reduces packet loss, end-to-end delay.