Secure and Energy Efficient Clustering and Routing Using Multi-Objective Trust Aware Cosine Tasmanian Devil Optimization Algorithm in WSN

Wireless Sensor Networks (WSNs) are a distributed group of Sensor Nodes (SN) that are dispersed geographically in the organized environment to monitor and collect data on environmental conditions.In the network, each node has a limited wireless transmission range hence it is significant for nodes to transfer data through intermediatory nodes to reach the destination, which is a Base Station (BS).However, energy consumption with secure communication is a primary challenge due to resource-constraint nature of device and its communication is unfriendly and open environment.This research proposes Multi-objective Trust-Aware Cosine Tasmanian Devil Optimization Algorithm (M-TACTDOA) to select the Secure Cluster Head (SCH) and routing path in WSN.The TDOA is improved by using Cosine Perturbation Differential Evolution mechanism (CPDE) which addresses local optima issue and rapid convergence speed.By applying fitness function, the M-TACTDOA determine and avoid malicious nodes which provides secure and reliable data transmission.The proposed M-TACTDOA achieves a less energy consumption of 0.08 J compared to existing techniques like Energy Optimization Routing by employing improved Artificial Bee Colony (EOR-iABC).