Genetic-Chicken Swarm Algorithm for Minimizing Energy in Wireless Sensor Network

Wireless Sensor Network (WSN) technology is the real-time application that growing rapidly as result of smart environments. Battery power one most significant resources in WSN. For enhancing a factor, clustering techniques are used. During forward data WSN, more consumed. In existing system, it works with Load Balanced Clustering Method (LBCM) and provides lifespan network scalability reliability. does not deal end-to-end delay delivery packets. overcoming these issues proposed Genetic Algorithm based on Chicken Swarm Optimization (GA-CSO) generates chromosomes an arbitrary method then values calculated using Fitness Function. (CSO) helps to solve complex optimization problems. Also, consists chickens, hens, rooster. It divides chicken into clusters. maintains energy during communication among sensor nodes also balances load gateways. The GA-CSO LBCM improves network. Moreover, minimizes consumption over outperforms by following metrics such efficiency, ratio packet delivery, throughput network, lifetime nodes. Therefore, evaluation shows efficiency has achieved 83.56% reached 99.12%. attained linear standard deviation reduced 97.32 ms.