Energy-efficient routing algorithm of dijkstra clustering and grey wolf optimization for wireless sensor networks
Jian Sun, Ying Xu, Quan Zhou · Engineering Research Express · 2025
Abstract Wireless Sensor Networks (WSNs) face critical challenges in energy utilization, cluster head distribution, and spatial organization, which collectively degrade network efficiency and operational longevity. To address these issues, we propose a routing algorithm integrating Dijkstra’s clustering technique with an enhanced Grey Wolf Optimization (GWO) framework. The protocol operates on randomly dispersed energy-constrained sensor nodes through two sequential phases: cluster formation and energy-aware routing. In the cluster formation phase, Dijkstra’s algorithm generates spatially balanced clusters by analyzing node positions and distribution density, mitigating the uneven energy depletion observed in conventional protocols like LEACH and KEAC. Within each cluster, a modified GWO algorithm selects optimal cluster heads by prioritizing residual energy and neighborhood connectivity, aligning with dynamic hierarchical optimization principles. For data transmission, a hybrid strategy combines single-hop intra-cluster communication with GWO-optimized multi-hop routing between cluster heads and the sink node. The enhanced GWO dynamically evaluates path quality based on nodal energy levels and depletion trends, improving upon static approaches. Comparative simulations demonstrate the protocol’s effectiveness in extending network lifetime and maintaining reliable data delivery across varying network scales.