GWO-SMSLO: Grey wolf optimization based clustering with secured modified Sea Lion optimization routing algorithm in wireless sensor networks

Wireless Sensor Networks (WSNs) is a distributed collection of sensor nodes which are employed to sense the natural phenomena from the environment which have been deployed. The sensed information is transmitted to the Base Station by using in network processing and collaborative processing. Due to the advancement of MEMS technology, WSN are applied in numerous applications including environment monitoring and military application for tracking and monitoring. However, the nodes of WSNs are deployed in harsh and unfriendly open environment and considering the resource constrained nature, providing efficient security with energy optimization is a major concern. To address the issues of energy optimization and security in this work Grey Wolf Optimization (GWO) has been employed to provide efficient clustering of the nodes and modified Sea Lion Optimization (SLO) has been employed to perform efficient routing. The security of the proposed scheme is ensured by Elliptic Curve Cryptography (ECC) by employing certificate less aggregate signature scheme with supporting conditional privacy. The simulation of the proposed protocol is carried out by using NS3 simulator with realistic simulation parameters. This simulation results shows that proposed protocol improves average energy consumption by 12%, packet delivery ratio by 8%, end to end delay by 15%, network lifetime by 15% and network throughput by 11% when it is compared with other existing protocols. Moreover, the proposed protocol improves security of the network by withstanding various malicious attacks in the network.