MEMETIC ALGORITHM-BASED IMPROVED LEACH (MA-ILEACH) FOR ENERGY-EFFICIENT AND LONG-LIFETIME WIRELESS SENSOR NETWORKS

Abstract

This paper presents a novel energy-efficient routing framework for Wireless Sensor Networks (WSNs) by integrating a Memetic Algorithm with the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol, termed MA-ILEACH. WSNs are widely deployed in applications such as environmental monitoring, industrial automation, and smart systems, where energy conservation and network longevity are critical challenges. Conventional LEACH suffers from random cluster head selection, uneven energy dissipation, and premature node failure. To address these limitations, the proposed approach employs a Memetic Algorithm combining global search through genetic operators and local refinement strategies to optimize cluster formation, cluster head selection, and routing paths. The MA-ILEACH algorithm introduces dynamic clustering and energy-aware routing mechanisms that adapt to changing network conditions. Simulation results, conducted using MATLAB across varying network sizes, demonstrate that the proposed model significantly reduces energy consumption, improves data transmission efficiency, and extends network lifetime compared to traditional LEACH and other existing protocols. The method achieves faster convergence and up to 69.3% reduction in computation time compared to standard genetic algorithms. Overall, the proposed approach offers a scalable and robust solution for next-generation energy-constrained WSN applications