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Article Dans Une Revue IEEE Sensors Letters Année : 2024

Semi-Decentralized Prediction Method for Energy-Efficient Wireless Sensor Networks

Résumé

[graphicalabstract] Addressing key challenges in Wireless Sensor Networks (WSNs) such as network lifetime, and energy balance, this paper introduces the Semi-Decentralized Prediction Method (SDPM) for energy-efficient wireless sensor networks. This approach enhances energy efficiency by combining clustering principles with data prediction for smart Cluster-Head (CH) selection. SDPM facilitates the periodic election of an effective CH from among the cluster-nodes, who then predicts data for the nodes within the cluster, thereby reducing transmission and conserving energy. Our findings demonstrate SDPM's significant impact on reducing energy consumption, promising for real-world WSNs to achieve longer network lifetime and better energy management.
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Dates et versions

hal-04512877 , version 1 (20-03-2024)

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Imourane Abdoulaye, Cécile Belleudy, Laurent Rodriguez, Benoît Miramond. Semi-Decentralized Prediction Method for Energy-Efficient Wireless Sensor Networks. IEEE Sensors Letters, 2024, pp.1-4. ⟨10.1109/LSENS.2024.3378520⟩. ⟨hal-04512877⟩
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