Intelligent unequal clustering in wireless sensor networks using a game theoretic and evolutionary strategy

Traditional clustering methods in Wireless Sensor Networks (WSNs) create energy distribution imbalances which shortens network operational time. The distribution of cluster heads becomes non-uniform because it does not respond to changes in node density or traffic patterns which leads to rapid energ...

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Veröffentlicht in:Scientific reports Jg. 15; H. 1; S. 32992 - 16
Hauptverfasser: Qu, Yanhui, Qu, Yingyi, Zhu, Zhiqiang, Deng, Liang, Xu, Xiao
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 26.09.2025
Nature Publishing Group
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Schlagworte:
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Algorithms
Clustering
Coyote optimization algorithm
Energy consumption
Energy efficiency
Environmental monitoring
Fuzzy logic
Game theory
Humanities and Social Sciences
Load distribution
Microelectromechanical systems
multidisciplinary
Optimization techniques
Protocol
Science
Science (multidisciplinary)
Sensors
Simulation analysis
Unequal clustering
Wireless communications
Wireless sensor networks
Fuzzy logic
Wireless sensor networks
Coyote optimization algorithm
Unequal clustering
Game theory
ISSN:2045-2322, 2045-2322
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Zusammenfassung:Traditional clustering methods in Wireless Sensor Networks (WSNs) create energy distribution imbalances which shortens network operational time. The distribution of cluster heads becomes non-uniform because it does not respond to changes in node density or traffic patterns which leads to rapid energy exhaustion among specific nodes while other nodes remain idle. The unequal clustering technique offers adaptive node distribution and traffic load balance in response to this problem. The proposed method selects cluster heads through Coyote Optimization Algorithm (COA) optimization while fuzzy logic controls the adaptive cluster radii according to network conditions. Energy-efficient data routing is made possible through the implementation of a game-theoretic approach. Simulation analysis shows significant performance gains. The proposed method outperformed traditional EE-LEACH by extending network lifetime by 124.5% through its implementation. The network operational duration increases because the intelligent energy consumption management system distributes loads evenly across different network conditions. The proposed intelligent unequal clustering method demonstrates great potential to improve WSN performance. The combination of dynamic clustering with optimized routing systems leads to major improvements of both energy efficiency and network reliability as well as lifetime extension.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-025-17758-9