An Efficient Fuzzy Logic Controller for Enhancing the Lifetime of Mobile WSNs Through Smart Cluster Head Selection Using Sleeping Time and Mobility Factor.
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| Title: | An Efficient Fuzzy Logic Controller for Enhancing the Lifetime of Mobile WSNs Through Smart Cluster Head Selection Using Sleeping Time and Mobility Factor. |
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| Authors: | Zaidi, Monji M.1,2,3,4 (AUTHOR) monji.zaidi@fsm.rnu.tn, Bouazzi, Imen R.1,4,5 (AUTHOR), Pandey, Kavita (AUTHOR) kavitapcse@gmail.com |
| Source: | International Journal of Distributed Sensor Networks. 4/13/2026, Vol. 2026, p1-18. 18p. |
| Subjects: | Wireless sensor networks, Clustering algorithms, Network performance, Fuzzy control systems, Energy consumption, Wireless sensor nodes |
| Abstract: | Wireless Sensor Networks (WSNs) are composed of energy‐constrained sensor nodes that often operate in dynamic and hard‐to‐access environments, where battery replacement is impractical and node mobility can significantly degrade network stability. Existing clustering‐based solutions frequently address either energy efficiency or mobility but rarely both in a unified and adaptive manner. Motivated by the need to simultaneously reduce energy consumption and ensure stable Cluster Head (CH) selection in mobile WSNs, this paper proposes an intelligent Fuzzy logic–based clustering framework that integrates residual energy, sleeping time, and mobility factor into the CH election process. Sleeping time is dynamically adjusted to reflect energy‐saving behavior, whereas mobility awareness prevents unstable nodes from being selected as CHs. MATLAB‐based simulation results demonstrate that the proposed approach significantly reduces energy consumption and extends network lifetime, achieving delayed node death and improved network stability compared to existing methods. This integrated design enables a unified and lightweight fuzzy framework suitable for resource‐constrained mobile WSNs. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Distributed Sensor Networks is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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