Abstract
A large number of spatially dispersed nodes on the wireless network create Wireless Sensor Networks (WSNs) to collect and analyze the physical data from the environment. The issues that affected the network and had an impact on network energy consumption were cluster head random selection, working node redundancy, and cluster head transmission path construction. Consequently, this energy constraint also has an impact on the network lifetime and energy-efficient routing. Therefore, the primary goals of this research are to decrease energy consumption and lengthen the network’s lifespan. So, using improved optimization algorithms, this paper presents a dynamic cluster head-based energy-efficient routing system. The Improved Coyote Optimization Algorithm (ICOA), in this case, consists of three phases setup, transmission, and measurement phase. The Improved Jaya Optimization Algorithm with Levy Flight (IJO-LF) then determines the route between the BS and the CH. It selects the most effective course based on the distance, node degree, and remaining energy. The proposed approach is compared with traditional methods and the routing protocols Power-Efficient Gathering in Sensor Information Systems (PEGASIS) and Threshold sensitive Energy Efficient Sensor Network protocol (TEEN) during implementation on the MATLAB platform. Performance indicators for the suggested methodology are evaluated based on data packets collected by the BS, energy usage, alive nodes, and dead nodes. The outputs of the suggested methodology performed better than the conventional plans.