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Using a neural network-based cluster head selection technique, this research presents an improved Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol for Wireless Sensor Networks (WSNs). In comparison to conventional LEACH techniques, the suggested framework maximizes energy efficiency and increases network longevity by including neural networks. According to simulations, our method greatly enhances cluster head selection, which leads to a longer network lifetime and more evenly distributed energy usage. The model architecture, simulation environment, and performance evaluation are all thoroughly examined, demonstrating a notable improvement in WSN sustainability and efficiency.

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Leveraging Neural Networks to Enhance Cluster Head Selection in the LEACH Protocol for Wireless Sensor Networks

  • 会议论文

  • 发表日期：

    2025年

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  • Monali Vishwakarma,
  • Devendra Kumar Meda

摘要

Using a neural network-based cluster head selection technique, this research presents an improved Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol for Wireless Sensor Networks (WSNs). In comparison to conventional LEACH techniques, the suggested framework maximizes energy efficiency and increases network longevity by including neural networks. According to simulations, our method greatly enhances cluster head selection, which leads to a longer network lifetime and more evenly distributed energy usage. The model architecture, simulation environment, and performance evaluation are all thoroughly examined, demonstrating a notable improvement in WSN sustainability and efficiency.