Gray Wolf‐Based Clustering for Enhanced Energy Efficiency in Wireless Sensor Networks

ABSTRACT Energy efficiency is a vital consideration in wireless sensor networks (WSNs) due to their limited energy resources. This study proposes the Gray Wolf‐Based Clustering for Enhanced Energy Efficiency (GWC‐EEE) protocol, which focuses on optimizing energy usage and extending network lifetime. GWC‐EEE employs a hierarchical network structure with a centralized clustering approach, where Gray Wolf Optimization (GWO) selects optimal cluster heads (CHs) based on an objective function. For data transmission, Ant‐based routing is implemented to identify energy‐efficient paths, whereas the MAC layer incorporates an improved CSMA/CA mechanism with dynamic sleep/activation scheduling to minimize collisions and reduce energy consumption. Simulation results demonstrate that GWC‐EEE outperforms existing state‐of‐the‐art techniques, achieving a 51% improvement in packet transmission to the CH and a 36% increase in packets delivered to the BS. Furthermore, it reduces energy dissipation across all evaluated techniques and enhances the packet delivery ratio (PDR) by 36% compared to other protocols. These results confirm that GWC‐EEE significantly improves network performance, optimizes data transmission, and minimizes energy consumption, making it a highly effective solution for WSNs.