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<p>Underwater Wireless Sensor Networks (UWSNs) face challenges such as limited bandwidth, higher delays, and dynamic topology due to water flow. Since it is not feasible to replace batteries, maximizing network lifetime becomes the key. In this scenario, a proposed two-stage algorithm, the UWSN routing method, is advanced to improve network longevity. Initially, sensor nodes gather neighbor information (residual energy, sweep angle, distance, packet delivery ratio) stored at the sink node. In the second stage, the proposed approach fuzzy hierarchy process (FHP) determines optimal next hops by assigning weight categories to different parameters and calculating cost function values for neighboring nodes. The node with the lowest cost function is chosen as the next hop, ensuring efficient routing. The algorithm also manages the broadcasting of updated energy levels: as a node’s energy decreases, it informs nearby nodes, aiding informed routing decisions based on energy availability. Numerical simulations suggest that the proposed approach will, on average, improve energy efficiency by up to 12% and network lifespan by approximately 6% compared with recent protocols, such as LE-VBF and DBR, with dead node occurrences reduced to 11% on average. The above results outline how well the given algorithm would increase the energy efficiency and operational lifetime of the considered UWSNs.</p>

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Energy efficient routing algorithm for UWSNs using Fuzzy sampling on nodes filtered by energy distribution analysis

  • 期刊论文

  • 发表日期：

    2025年7月31日

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  • Solagudi Navya,
  • G. Thavasi Raja,
  • B. Shameedha Begum

摘要

Underwater Wireless Sensor Networks (UWSNs) face challenges such as limited bandwidth, higher delays, and dynamic topology due to water flow. Since it is not feasible to replace batteries, maximizing network lifetime becomes the key. In this scenario, a proposed two-stage algorithm, the UWSN routing method, is advanced to improve network longevity. Initially, sensor nodes gather neighbor information (residual energy, sweep angle, distance, packet delivery ratio) stored at the sink node. In the second stage, the proposed approach fuzzy hierarchy process (FHP) determines optimal next hops by assigning weight categories to different parameters and calculating cost function values for neighboring nodes. The node with the lowest cost function is chosen as the next hop, ensuring efficient routing. The algorithm also manages the broadcasting of updated energy levels: as a node’s energy decreases, it informs nearby nodes, aiding informed routing decisions based on energy availability. Numerical simulations suggest that the proposed approach will, on average, improve energy efficiency by up to 12% and network lifespan by approximately 6% compared with recent protocols, such as LE-VBF and DBR, with dead node occurrences reduced to 11% on average. The above results outline how well the given algorithm would increase the energy efficiency and operational lifetime of the considered UWSNs.