A Novel EKH-LEACH Algorithm for Energy Optimization in IoT Wireless Sensor Networks

Abstract

The Internet of Things (IoT) has revolutionized the electronic world by integrating numerous independent sensors capable of remote sensing and interaction. Wireless Sensor Networks (WSNs) form the backbone of IoT, providing extensive connectivity among resource-constrained nodes. However, energy efficiency remains a critical design challenge in WSNs due to the limited battery capacity of sensor nodes. This paper introduces a novel Enhanced Krill Herd-based LEACH (EKH-LEACH) algorithm for optimizing energy usage in IoT-driven WSNs. The EKH-LEACH protocol enhances the traditional LEACH algorithm by incorporating an improved Krill Herd (KH) optimization technique to select cluster heads (CHs) more effectively. By leveraging a suitability function that combines neighborhood distance with KH optimization, the proposed algorithm significantly improves energy efficiency and extends the network's lifetime. Experimental evaluations demonstrate that EKH-LEACH outperforms conventional methods in terms of average energy consumption, standard deviation of energy distribution, and overall network performance. This novel approach offers a robust solution for energy optimization in IoT-based WSNs, ensuring sustainable and efficient network operations.