An Energy Optimization Algorithm for WRSN Nodes Based on Regional Partitioning and Inter-Layer Routing

In large-scale Wireless Rechargeable Sensor Networks (WRSN), traditional forward routing mechanisms often lead to reduced energy efficiency. To address this issue, this paper proposes a WRSN node energy optimization algorithm based on regional partitioning and inter-layer routing. The algorithm employs a dynamic clustering radius method and the K-means clustering algorithm to dynamically partition the WRSN area. Then, the cluster head nodes in the outermost layer select an appropriate layer from the next relay routing region and designate it as the relay layer for data transmission. Relay nodes are selected layer by layer, starting from the outermost cluster heads. Finally, the inter-layer routing mechanism is integrated with regional partitioning and clustering methods to develop the WRSN energy optimization algorithm. To further optimize the algorithm’s performance, we conduct parameter optimization experiments on the relay routing selection function, cluster head rotation energy threshold, and inter-layer relay structure selection, ensuring the best configurations for energy efficiency and network lifespan. Based on these optimizations, simulation results demonstrate that the proposed algorithm outperforms traditional forward routing, K-CHRA, and K-CLP algorithms in terms of node mortality rate and energy consumption, extending the number of rounds to 50% node death by 11.9%, 19.3%, and 8.3% in a 500-node network, respectively.