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<p>In recent years, deep-sea acoustic sensor networks (DSASNs) have gained considerable attention in areas such as deep-sea resource exploration, environmental monitoring, and underwater construction. However, due to the combined effects of adverse DSA channel conditions, a hostile deep-sea environment, long propagation delays, and limited energy supply, DSASNs often experience random performance fluctuations and low resilience. These issues are typically caused by unstable connectivity and abnormal node failures. Given the critical role of network topology in influencing network behavior, this paper proposes a hybrid topology optimization algorithm for DSASNs. The algorithm integrates the virtual force algorithm (VFA) and particle swarm optimization (PSO), leveraging the global search capability of PSO and the local optimization strength of VFA to provide a highly robust solution for improving the DSASN resilience (DSR-VFPSO). Specifically, a comprehensive objective function is formulated to transform the high-resilience topology optimization problem into a dual-objective function of maximizing coverage and optimizing betweenness centrality. This objective is addressed iteratively through the combined use of VFA and PSO to reach an optimal solution. Simulation results reveal that the proposed algorithm effectively improves the resilience of DSASNs under artificial stress conditions caused by random node failures.</p>

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Hybrid Optimization of Deep-Sea Acoustic Sensor Network Topology for Enhancing Resilience

  • 期刊论文

  • 发表日期：

    2025年9月18日

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  • Wenmin Lin,
  • Shuaifeng Hao,
  • Dongsheng Chen,
  • Feng Tong,
  • Peichen Niu

摘要

In recent years, deep-sea acoustic sensor networks (DSASNs) have gained considerable attention in areas such as deep-sea resource exploration, environmental monitoring, and underwater construction. However, due to the combined effects of adverse DSA channel conditions, a hostile deep-sea environment, long propagation delays, and limited energy supply, DSASNs often experience random performance fluctuations and low resilience. These issues are typically caused by unstable connectivity and abnormal node failures. Given the critical role of network topology in influencing network behavior, this paper proposes a hybrid topology optimization algorithm for DSASNs. The algorithm integrates the virtual force algorithm (VFA) and particle swarm optimization (PSO), leveraging the global search capability of PSO and the local optimization strength of VFA to provide a highly robust solution for improving the DSASN resilience (DSR-VFPSO). Specifically, a comprehensive objective function is formulated to transform the high-resilience topology optimization problem into a dual-objective function of maximizing coverage and optimizing betweenness centrality. This objective is addressed iteratively through the combined use of VFA and PSO to reach an optimal solution. Simulation results reveal that the proposed algorithm effectively improves the resilience of DSASNs under artificial stress conditions caused by random node failures.