Multi Objective-Trust Aware Coati Optimization Algorithm for Secure Cluster Head and Route Discovery in IoT-WSN
International journal of intelligent engineering and systems · 2024
Internet of Things (IoT) is a network of physical objects generally utilized for interconnecting and communicating with other devices via the Internet.Here, Wireless Sensor Network (WSN) is used as a medium to connect the IoT physics and information network.Security is considered as an important aspect in IoT-WSN due to the open deployment of sensors.In this research, a Multi Objective-Trust Aware Coati Optimization Algorithm (MO-TACOA) is proposed to perform secure and reliable data communication over the IoT-WSN under malicious attacks.Initially, the Secure Cluster Head (SCH) from the normal sensors are chosen by optimizing the MO-TACOA with trust, residual energy, interspace between sensors & SCH, interspace between SCH & BS, and node degree.Next, the secure path is identified by optimizing the MO-TACOA with residual energy and interspace between SCH & BS.Therefore, the proposed MO-TACOA improves the security against malicious attacks while also improving the data delivery.The MO-TACOA is evaluated using alive nodes, energy expenditure, lifecycle, throughput and Packet Loss Ratio (PLR).The existing methods namely, Taylor based Cat Salp Swarm Algorithm (Taylor C-SSA), Taylor-Spotted Hyena Optimization (TaylorSHO) and Beet swarm Induced Tunicate swarm Algorithm (BITA) are used for comparison.The MO-TACOA achieves the throughput of 16087 kbps which is higher than that of the TaylorSHO.