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<p>In the last couple of decades, the functional area of underwater wireless sensor networks (UWSNs) has widened, though these networks are burdened with unique problems such as a lack of GPS, high-energy usage, long propagation delay, and limited bandwidth. UWSNs use acoustic communication, which requires higher-power consumption compared to terrestrial networks. This research proposes a new energy-efficient routing strategy using the hybrid fuzzy clustering technique in UWSNs. The recommended methodology applies fuzzy logic to dynamically choose cluster heads with various parameters like residual energy, node distance, and data load to enhance load distribution among nodes and minimize energy expenditure. Simulation results prove that the protocol outperforms the DABC and IDACB algorithms by reducing routing packets by 29% and enhancing the packet delivery ratio by 19%. Besides, the new scheme improved energy variance by 40% at nodes to prolong the network lifetime and maintain a higher throughput in conditions of variable network load. This fuzzy clustering technique stands apart because it tries to overcome UWSN-specific challenges using adaptive data aggregation along with multistep communication and hence is more resistant and energy-efficient compared to the conventional protocols.</p>

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A new method for routing protocols using hybrid fuzzy clustering in UWSNs

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月9日

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  • Xiaoju Wang,
  • Bin Meng,
  • Xuexu Yuan,
  • Junwei Zhao

摘要

In the last couple of decades, the functional area of underwater wireless sensor networks (UWSNs) has widened, though these networks are burdened with unique problems such as a lack of GPS, high-energy usage, long propagation delay, and limited bandwidth. UWSNs use acoustic communication, which requires higher-power consumption compared to terrestrial networks. This research proposes a new energy-efficient routing strategy using the hybrid fuzzy clustering technique in UWSNs. The recommended methodology applies fuzzy logic to dynamically choose cluster heads with various parameters like residual energy, node distance, and data load to enhance load distribution among nodes and minimize energy expenditure. Simulation results prove that the protocol outperforms the DABC and IDACB algorithms by reducing routing packets by 29% and enhancing the packet delivery ratio by 19%. Besides, the new scheme improved energy variance by 40% at nodes to prolong the network lifetime and maintain a higher throughput in conditions of variable network load. This fuzzy clustering technique stands apart because it tries to overcome UWSN-specific challenges using adaptive data aggregation along with multistep communication and hence is more resistant and energy-efficient compared to the conventional protocols.