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This paper introduces a Mobility-Aware Weighted Clustering Algorithm (MAWCA) designed to optimize the selection of cluster heads (CH) for mobile nodes in IoT networks by efficiently harvesting routing energy. MAWCA incorporates multiple factors such as node degree difference, discrepancies among neighbors, cumulative time, node mobility, and delay as weighting elements in the CH election process. To further enhance energy efficiency and ensure secure communication, the study integrates an Energy-Aware and Secure Multi-Hop Routing (ESMR) protocol, which employs a secret sharing mechanism. Additionally, the proposed approach performs a quantitative analysis of data connections to reduce routing disruption and improve overall network performance. The research aims to provide a lightweight yet effective solution for IoT-based wireless sensor networks (WSNs), facilitating efficient and secure multi-hop data routing while extending the network’s operational lifespan. Through comprehensive simulations and evaluations, the proposed methods demonstrate significant improvements in energy efficiency, security, and network stability, making them highly suitable for resource-constrained IoT environments.

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Optimizing IoT Network Performance: Mobility-Aware Clustering and Energy-Efficient Multi-Hop Routing Using WSNs

  • 会议论文

  • 发表日期：

    2025年

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  • G. Mariya Gnana Merlin,
  • R. Prema,
  • K. Thangavel,
  • A. Dhina Infant Maria,
  • K. Sathiyaseelan

摘要

This paper introduces a Mobility-Aware Weighted Clustering Algorithm (MAWCA) designed to optimize the selection of cluster heads (CH) for mobile nodes in IoT networks by efficiently harvesting routing energy. MAWCA incorporates multiple factors such as node degree difference, discrepancies among neighbors, cumulative time, node mobility, and delay as weighting elements in the CH election process. To further enhance energy efficiency and ensure secure communication, the study integrates an Energy-Aware and Secure Multi-Hop Routing (ESMR) protocol, which employs a secret sharing mechanism. Additionally, the proposed approach performs a quantitative analysis of data connections to reduce routing disruption and improve overall network performance. The research aims to provide a lightweight yet effective solution for IoT-based wireless sensor networks (WSNs), facilitating efficient and secure multi-hop data routing while extending the network’s operational lifespan. Through comprehensive simulations and evaluations, the proposed methods demonstrate significant improvements in energy efficiency, security, and network stability, making them highly suitable for resource-constrained IoT environments.