Comparative Analysis of PSO vs. GWO-Enhanced LEACH in Energy-Efficient Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are extensively used in applications such as environmental monitoring, surveillance, and smart security, but their performance is limited by the restricted energy capacity of sensor nodes, particularly in remote deployments. Efficient cluster head (CH) selection is therefore essential to extend network lifetime and maintain reliable data transmission. This paper presents a comparative study of the conventional Low Energy Adaptive Clustering Hierarchy (LEACH) protocol and its bio-inspired variants based on Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO). The proposed approach integrates energy-aware fitness functions into the LEACH setup phase while preserving the standard data transmission process. Simulation results show that PSO-LEACH improves network stability by approximately 25% and increases throughput by nearly 18% compared to standard LEACH. GWO-LEACH achieves superior performance, extending overall network lifetime by about 40% and maintaining a higher number of active nodes throughout the simulation. The core finding indicates GWO-based CH selection significantly enhances energy efficiency and network longevity over conventional LEACH.

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Publication Details

Journal
Journal of Applied Science & Process Engineering
Published
2026-04-30
DOI
https://doi.org/10.33736/jaspe.10167.2026
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
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article

Comparative Analysis of PSO vs. GWO-Enhanced LEACH in Energy-Efficient Wireless Sensor Networks

Devika G
Journal of Applied Science & Process Engineering
Energy Efficient Wireless Sensor Networks
article

Comparative Analysis of PSO vs. GWO-Enhanced LEACH in Energy-Efficient Wireless Sensor Networks

Devika G
article en

Abstract

Wireless Sensor Networks (WSNs) are extensively used in applications such as environmental monitoring, surveillance, and smart security, but their performance is limited by the restricted energy capacity of sensor nodes, particularly in remote deployments. Efficient cluster head (CH) selection is therefore essential to extend network lifetime and maintain reliable data transmission. This paper presents a comparative study of the conventional Low Energy Adaptive Clustering Hierarchy (LEACH) protocol and its bio-inspired variants based on Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO). The proposed approach integrates energy-aware fitness functions into the LEACH setup phase while preserving the standard data transmission process. Simulation results show that PSO-LEACH improves network stability by approximately 25% and increases throughput by nearly 18% compared to standard LEACH. GWO-LEACH achieves superior performance, extending overall network lifetime by about 40% and maintaining a higher number of active nodes throughout the simulation. The core finding indicates GWO-based CH selection significantly enhances energy efficiency and network longevity over conventional LEACH.

Journal of Applied Science & Process EngineeringVol. 13(1)
Government of Karnataka (IN)
Affordable and clean energy
Openalex Percentile: Top 11%
Energy Efficient Wireless Sensor Networks
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