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<p>Wireless sensor networks encompass spatially distributed sensor nodes that autonomously monitor and gather information from physical or environmental conditions. These networks faced notable difficulties such as energy effectiveness, scalability, and reliable data transmission, which influence directly their functional lifespan and overall performance. Hence, this study explores a novel routing framework for an energy-efficient wireless sensor network. The clustering and routing strategy is developed for optimizing the overall network lifetime and minimizing energy utilization. The novel Hybrid Adaptive Archimedes Marine Predator-based Multipath Routing algorithm is proposed in this research, which optimizes cluster head selection and data transmission. The data are gathered from various regions using sensor nodes that are aggregated by utilizing cluster heads. The proposed algorithm selects the most appropriate cluster heads according to energy levels and node characteristics. The system reduces energy utilization and confirms effective communication between sensor nodes and the base station. Furthermore, the localization and cluster formation minimize communication overhead and prolong the functional lifetime of the network. In addition, the multipath routing mechanism provides an alternative path for data transmission, enhancing network reliability and minimizing possibility of node failure. The experimental validation is performed to analyze the performances by using key measures. The performance of the proposed algorithm exhibits the finest performances such as packet drop rate of 13%, throughput of 14×10<sup>4</sup>Mbps, number of alive nodes of 138, number of send packets of 3×10<sup>6</sup>packets, network lifetime of 3.3×10<sup>4</sup>ms, security rate of 98%, end-to-end delay of 170ms, latency of 118ms, number of dead nodes of 12, execution time of 1.4ms, detection accuracy of 98.68%, True Positive Rate of 98.9%, False positive Rate of 96.3%, F1-score of 98.19% and energy consumption of 32J, demonstrating its efficiency in energy-constraint environments. The proposed algorithm helps to enhance the efficiency, reliability, and security of the wireless sensor network during data transmission.</p>

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Energy-efficient wireless sensor networks: A novel hybrid adaptive archimedes marine predator-based routing strategy

  • 期刊论文

  • 发表日期：

    2025年12月11日

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  • S. Mathupriya,
  • A. Chinnasamy,
  • Sathies Kumar Thangarajan

摘要

Wireless sensor networks encompass spatially distributed sensor nodes that autonomously monitor and gather information from physical or environmental conditions. These networks faced notable difficulties such as energy effectiveness, scalability, and reliable data transmission, which influence directly their functional lifespan and overall performance. Hence, this study explores a novel routing framework for an energy-efficient wireless sensor network. The clustering and routing strategy is developed for optimizing the overall network lifetime and minimizing energy utilization. The novel Hybrid Adaptive Archimedes Marine Predator-based Multipath Routing algorithm is proposed in this research, which optimizes cluster head selection and data transmission. The data are gathered from various regions using sensor nodes that are aggregated by utilizing cluster heads. The proposed algorithm selects the most appropriate cluster heads according to energy levels and node characteristics. The system reduces energy utilization and confirms effective communication between sensor nodes and the base station. Furthermore, the localization and cluster formation minimize communication overhead and prolong the functional lifetime of the network. In addition, the multipath routing mechanism provides an alternative path for data transmission, enhancing network reliability and minimizing possibility of node failure. The experimental validation is performed to analyze the performances by using key measures. The performance of the proposed algorithm exhibits the finest performances such as packet drop rate of 13%, throughput of 14×104Mbps, number of alive nodes of 138, number of send packets of 3×106packets, network lifetime of 3.3×104ms, security rate of 98%, end-to-end delay of 170ms, latency of 118ms, number of dead nodes of 12, execution time of 1.4ms, detection accuracy of 98.68%, True Positive Rate of 98.9%, False positive Rate of 96.3%, F1-score of 98.19% and energy consumption of 32J, demonstrating its efficiency in energy-constraint environments. The proposed algorithm helps to enhance the efficiency, reliability, and security of the wireless sensor network during data transmission.