A Jellyfish Search Optimization-Based Energy-Efficient LEACH Protocol for Scalable Wireless Sensor Networks

Abstract

Large-scale Wireless Sensor Networks (WSNs) require routing strategies that can simultaneously preserve energy, maintain reliable packet delivery, and remain stable as node density increases. Conventional LEACH reduces direct communication through clustering, but its randomized cluster-head selection can cause uneven energy depletion and frequent control activity. This paper presents a completely revised Energy-Optimized LEACH (EOL) framework that combines proximity-aware path selection, Jellyfish Search Optimization (JSO)-assisted cluster-head selection, and residual-energy-based transmission coordination. The framework is designed to balance routing quality against the computational cost of repeated optimization. The reported evaluation uses NS-2.35, static deployments from 25 to 200 nodes, a 100 m × 100 m sensing region, 20 independent runs, and paired statistical analysis. Relative to conventional LEACH, the source experimental results show a 13.33% improvement in packet delivery ratio, a 17.79% reduction in packet loss ratio, a 10.49% reduction in end-to-end delay, a 39.49% improvement in throughput, a 16.35% reduction in routing overhead, and a 10.89% reduction in average energy consumption. The revised paper reorganizes the methodology around a unified optimization objective, separates the roles of routing, clustering, and transmission control, and presents the results with a consistent comparative narrative. The findings indicate that integrating energy-aware clustering with lightweight route selection can improve communication efficiency in dense WSN scenarios while retaining practical scalability.