Energy Saving Algorithm of Wireless Sensor Networks with Improved Zebra Optimization Algorithm

In this paper, an energy-saving optimization algorithm EZOAG based on improved Zebra optimization algorithm is proposed to solve the problems of high energy consumption and short network life of traditional LEACH clustering algorithm in wireless sensor networks. In the clustering stage, the elite reverse learning algorithm and the golden sine algorithm are combined into the ZOA algorithm to achieve more efficient clustering. In the cluster head selection phase, an energy-feedback-based mechanism is introduced to optimize the cluster head selection process. In the data transmission phase, an undirected graph is constructed to model the energy consumption between the cluster head and the sink node, and the Dijkstra algorithm is used to determine the optimal transmission path, further minimizing the energy consumption of the cluster head. Simulation results show that compared to LEACH, GWO, PSO, and ZOA algorithms, the EZOAG algorithm significantly reduces network energy consumption and extends the network's operational lifetime.