EEZR-CGeHBSLoA: Energy-Efficient Hybrid Dynamic Zone-Based Multiple Cluster Head Selection and Routing in Border Surveillance WSNs

In wireless sensor networks (WSNs), restricted design constraints of sensor nodes imposes difficult challenges in enhancing network lifetime and connectivity. Especially, power constraints of these sensor nodes plays crucial role in determining network connectivity, lifetime and overall performance. In order to conserve limited power of nodes, network related activities should be balanced and each node has to equally dissipate its energy to ensure node’s aliveness. Thus, effectively utilizing the available limited battery energy is given primary importance in WSN research works. Likewise, we introduce a hybrid approach called an Energy-Efficient Zone Routing with Cluster Geometric Honey Badger SeaLion Optimization Algorithm (EEZR-CGeHBSLoA) designed to improve WSN performance through dynamic clustering and intelligent routing strategies. Unlike conventional clustering methods, EEZR-CGeHBSLoA employs geometric symmetry-based zone coordinators to adaptively segment the sensing area into energy-efficient zones, ensuring optimal cluster formation. To facilitate balanced energy consumption, this approach utilizes the enhanced Honey Badger Algorithm for selecting multiple cluster heads for each zone. The CH selection process considers residual energy, proximity to the base station, and node connectivity, thereby preventing premature energy depletion to improve network longevity. Simulations were conducted to evaluate EEZR-CGeHBSLoA’s performance in comparison with existing WSN clustering protocols where results proved that the proposed model achieved a network lifespan of 2473 rounds, an average energy consumption rate of 11.3%, and a packet reception rate of 98.11%. Therefore, EEZR-CGeHBSLoA method has significantly enhanced network robustness, mitigated packet loss, and improved overall data transmission reliability.