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Article type: Research Article
Authors: Akbas, Ayhana | Buyrukoglu, Goncab | Buyrukoglu, Selimc; *
Affiliations: [a] Institute for Communication Systems, University of Surrey, Guildford, GU2 7XH, UK | [b] Department of Statistics, Cankiri Karatekin University, Cankiri, Turkey | [c] Computer Engineering Department, Cankiri Karatekin University, Cankiri, Turkey
Correspondence: [*] Corresponding author. Selim Buyrukoglu, Computer Engineering Department, Cankiri Karatekin University, Cankiri, 18100, Turkey. E-mail: [email protected].
Abstract: Wireless Sensor Networks (WSNs) have garnered significant attention from both the academic and industrial communities. However, the limited battery capacity of WSN nodes imposes a set of restrictions on energy dissipations, which has compelled researchers to seek ways to save and minimize energy consumption. This paper presents a hybrid optimization model to minimize energy dissipation in Wireless Sensor Networks (WSNs). Employing linear programming and a combination of XGBoost and Random Forest algorithms, it effectively predicts internode distances and network lifetime. The results demonstrate significant energy savings in WSN deployments, outperforming traditional methods. This approach contributes to the field by offering a practical, energy-efficient strategy for WSN configuration planning, highlighting the model’s applicability in real-world scenarios, where energy conservation is critical.
Keywords: Wireless sensor networks, energy minimization, linear programming, optimization model, XGBoost, random forest
DOI: 10.3233/JIFS-234798
Journal: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2024
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