An Effective Trusted and Secure based Clustering and Routing using Improved Bat Optimization Algorithm

Security measures contribute to the overall longevity of the Wireless Sensor Network (WSN) by preventing attacks that could lead to node compromise or depletion of energy resources. WSNs operate in dynamic environments, necessitating adaptable secure clustering algorithms that can effectively respond to frequent changes in network topology. In this work, we introduce the Improved Bat Optimization algorithm (IBOA) for secure clustering and routing in WSN. We subsequently apply the secure-based trust protocol to transmit data on the secured path. The fitness function is obtained by utilizing the well-defined limitations named energy, delay, security, as well as distance. The proposed method achieves better results and attains an energy consumption of 0.1 (J), an average delay of 0.1 sec, Packet Delivery Ratio (PDR) of 97.5%, and throughput of 80% at the number of nodes of 100 respectively when compared to existing methods such as Dempster-Shafer Theory-based Lion Optimization Algorithm clustering (DST-LOA) and Energy Competent Particle Swarm Optimization depending on the Passive Clustering Mechanism (ECPSO-PCM).