A Metaheuristic-Driven Energy-Optimized LEACH Protocol for QoS-Aware and Scalable Routing in Heterogeneous WSNs

Abstract

 Efficient routing and energy management remain critical challenges in Wireless Sensor Networks (WSNs) due to limited energy resources, dynamic topology, and scalability requirements. This paper proposes a novel Energy Optimized LEACH (EOL) protocol that integrates Optimized Proximity Function (OPF)-based distance-aware routing, Jellyfish Search Optimization (JSO)-based energy-aware clustering, and adaptive transmission control into a unified multi-objective optimization framework. Unlike conventional LEACH and standalone metaheuristic-based approaches, the proposed method simultaneously optimizes routing efficiency, energy balancing, and transmission adaptability. The performance of EOL is evaluated against classical LEACH and JSO-based protocols across network sizes ranging from 25 to 200 nodes using key performance metrics including PDR, PLR, delay, throughput, routing overhead, and energy consumption. Experimental results demonstrate that EOL achieves 13.33% higher PDR, reduces PLR by 17.79%, lowers delay by 10.49%, improves throughput by 39.49%, and reduces energy consumption by 10.89% compared to LEACH. These improvements are primarily attributed to efficient cluster-head selection, distance-aware routing, and adaptive transmission control. The results confirm that EOL provides a scalable, energy-efficient, and QoS-aware routing solution suitable for heterogeneous WSN environments.