Dynamic Candidate Solution and Elite Opposite Based Kookaburra Optimization Algorithm for Energy Efficient Routing in Wireless Sensor Network

A Wireless Sensor Network (WSN) is a self-organizing network consisting of numerous small Sensor Nodes (SNs) to monitor a wide range of applications.However, existing methods suffer from high energy consumption and delays, which reduce network lifetime.This research proposes a Dynamic Candidate Solution and Elite Oppositebased Kookaburra Optimization Algorithm (DEOKOA) for energy-efficient Cluster Head (CH) and route path selection in WSNs.The DEOKOA is designed to achieve an optimal balance between exploration and exploitation, thereby avoiding issues related to trapping in local optima.Fitness functions such as residual energy, inter-node spacing, node degree, node centrality, and the Cluster Head Balancing Factor (CHBF) are employed to enhance data transmission in WSNs.Network Lifetime (NLT), Packet Delivery Ratio (PDR), Energy Consumption (EC), throughput, and delay are considered to evaluate DEOKOA's performance.The DEOKOA achieves an EC of 39.86mJ, a delay of 3.36ms, and an NLT of 4800 rounds for 1000 nodes, outperforming the existing Adaptive Remora Optimization Algorithm (AROA).