Wandering Strategy–Sand Cat Swarm Optimization-Based Energy Efficient Underwater Wireless Sensor Network

Underwater Wireless Sensor Network (UWSN) includes a numerous number of sensors positioned in oceans and rivers to observe in underwater environment. Though, underwater sensors are limited for energy and that is tedious for replacing a battery, resulted in energy efficient is main problem. For clustering and routing, in this research proposed a Wandering Strategy – Sand Cat Swarm optimization (WS-SCSO) algorithm which enhanced network lifetime. The WS-SCSO algorithm selects the appropriate Cluster Head (CH) for network and then generates a cluster. Then, by using WS-SCSO algorithm identifies a suitable route for nodes that transmits a data. The proposed algorithm enhances a network lifetime with less energy consumption. The evaluation metrics used to evaluate proposed algorithm are alive nodes, dead nodes, total energy consumption and packet delivery ratio. The proposed algorithm attained less energy consumption of 3% at 200 rounds, 7% at 400 rounds, 18% at 600, 31% at 800 rounds and 55% at 1000 rounds which is effective than previous optimization algorithms like Improved Metaheuristics based Clustering with Multihop Routing protocol (IMCMR-UWSN).