An Energy-Efficient Clustering Routing Protocol Based on Genetic Algorithm for Wireless Sensor Networks

International Journal of Computer Science and Technology | Vol. 1, No. 1, January 2020 | pp. 1–8

Research Article

Title: An Energy-Efficient Clustering Routing Protocol Based on Genetic Algorithm for Wireless Sensor Networks

Names of Authors: Amina Bello¹, Chinedu Okafor², and Oluwaseun Adebayo³

Authors’ Affiliations:
¹Department of Computer Science, University of Lagos, Lagos, Nigeria
²Department of Electrical and Computer Engineering, Federal University of Technology, Minna, Nigeria
³Department of Computer Engineering, Covenant University, Ota, Nigeria

Abstract: Wireless sensor networks (WSNs) face significant performance constraints due to limited battery energy in individual sensor nodes. Uneven energy dissipation rapidly depletes network nodes, leading to premature network partitioning and reduced operational lifespan. Traditional routing approaches often fail to balance energy consumption across dynamic topologies, resulting in inefficient data transmission paths. This paper proposes an optimized, energy-efficient clustering routing protocol leveraging a genetic algorithm (GA) to maximize the overall lifetime of large-scale WSNs. The core methodology formulates a multi-objective fitness function incorporating residual node energy, distance to the base station, and local node density to select optimal cluster heads dynamically. Chromosome encoding and genetic operators, including roulette-wheel selection, single-point crossover, and bit-mutation, are iteratively executed to avoid local optima convergence during cluster head formation. Simulation results conducted in a randomized deployment area of 100m x 100m demonstrate that the proposed GA-based protocol reduces average energy consumption per round by 28.5% compared to standard Low-Energy Adaptive Clustering Hierarchy (LEACH) and Power-Efficient Gathering in Sensor Information Systems (PEGASIS) algorithms. Furthermore, the time to first node death (FND) is extended by 34.2%, and total packet delivery ratio improves significantly under high traffic loads. The findings confirm that genetic algorithm-driven optimization provides a robust framework for prolonging network longevity and maintaining reliable connectivity in resource-constrained industrial and environmental monitoring applications.

Keywords: Wireless sensor networks, Energy efficiency, Clustering routing, Genetic algorithm, Network lifetime, Optimization

Manuscript Timeline: Received: October 14, 2019; Revised: November 22, 2019; Accepted: December 10, 2019; Published: January 5, 2020

Citation: Bello, A., Okafor, C., & Adebayo, O. (2020). An energy-efficient clustering routing protocol based on genetic algorithm for wireless sensor networks. International Journal of Computer Science and Technology, 1(1), 1–8. DOI: 10.46882/2020/IJCST/000001

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