EEL-GA: an evolutionary clustering framework for energy-efficient 3D wireless sensor networks in smart forestry
Article
Batool, F., Ali, K., Lasebae, A., Windridge, D. and Kiyani, A. 2025. EEL-GA: an evolutionary clustering framework for energy-efficient 3D wireless sensor networks in smart forestry. Sensors. 25 (17). https://doi.org/10.3390/s25175250
| Type | Article |
|---|---|
| Title | EEL-GA: an evolutionary clustering framework for energy-efficient 3D wireless sensor networks in smart forestry |
| Authors | Batool, F., Ali, K., Lasebae, A., Windridge, D. and Kiyani, A. |
| Abstract | Wireless Sensor Networks (WSNs) are very important for monitoring complex 3D environments like forests, where energy efficiency and reliable communication are critical. This paper presents EEL-GA, an Energy Efficient LEACH-based clustering protocol optimized using a Genetic Algorithm. Cluster head (CH) selection is guided by a dual-metric fitness function combining residual energy and intra-cluster distance. EEL-GA is evaluated against EEL variants using Particle Swarm Optimization (PSO), Differential Evolution (DE), and the Artificial Bee Colony (ABC) across key performance metrics, including energy efficiency, packet delivery, and cluster lifetime. Simulations using real environmental data confirm EEL-GA’s superiority in sustaining energy, minimizing delay, and improving network stability, making it ideal for smart forestry and mission-critical WSN deployments. The model also incorporates environmental dynamics, such as temperature and humidity, enhancing its robustness in real-world applications. These findings support EEL-GA as a scalable, adaptive solution for future energy-aware 3D WSN frameworks. |
| Sustainable Development Goals | 9 Industry, innovation and infrastructure |
| Middlesex University Theme | Creativity, Culture & Enterprise |
| Publisher | MDPI |
| Journal | Sensors |
| ISSN | |
| Electronic | 1424-8220 |
| Publication dates | |
| Online | 23 Aug 2025 |
| 23 Aug 2025 | |
| Publication process dates | |
| Submitted | 02 Jul 2025 |
| Accepted | 20 Aug 2025 |
| Deposited | 12 Sep 2025 |
| Output status | Published |
| Publisher's version | License File Access Level Open |
| Copyright Statement | © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
| Digital Object Identifier (DOI) | https://doi.org/10.3390/s25175250 |
| PubMed ID | 40942680 |
| PubMed Central ID | PMC12431118 |
| Web of Science identifier | WOS:001570099400001 |
| National Library of Medicine ID | 101204366 |
https://repository.mdx.ac.uk/item/2qywz4
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