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<p>This paper introduces FERDOSI (Fog-Based Energy-Efficient Reliable Detection of Ocean Submarine Disaster in IoUT/IoO), a novel and energy-efficient framework for underwater communication, specifically designed for reliable detection of submarine disasters within the Internet of Underwater Things (IoUT). FERDOSI introduces a hybrid network architecture combining Software-Defined Networking (SDN) and fog computing principles for a resilient underwater submarine landslide-related coastal disaster early warning system. The architecture employs a hierarchical control model, with a centralized SDN controller providing global network management and multiple fog nodes overseeing localized sensor groups. Each sensor node assesses its energy requirements for sending/receiving data before sending information to the local fog controller. Local controllers discover all possible routes and calculating the path energy. Stability analysis, using standard deviation, is performed by the high-level controller to assess and remove paths with fluctuation in energy. The high-level controller uses <i>Z</i>-score and IQR to find outlier routes and filters them out. The high-level controller computes a minimum number of shortest paths to achieve a target reliability. Then, it applies a weighted variance to prioritize critical nodes and Markov chain to define transmission success probability. This integrated approach offers a highly efficient and reliable network by leveraging centralized control with edge intelligence. Simulation results demonstrate that FERDOSI significantly outperforms existing approaches, exhibiting lower latency, reduced packet loss, enhanced throughput, and decreased energy consumption across varying data load conditions, demonstrating the potential to deliver timely data for critical applications.</p>

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FERDOSI: fog-based energy-efficient reliable detection of ocean submarine disaster in IoUT/IoO

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月15日

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  • Shahrzad Sedaghat,
  • Amir Hossein Jahangir

摘要

This paper introduces FERDOSI (Fog-Based Energy-Efficient Reliable Detection of Ocean Submarine Disaster in IoUT/IoO), a novel and energy-efficient framework for underwater communication, specifically designed for reliable detection of submarine disasters within the Internet of Underwater Things (IoUT). FERDOSI introduces a hybrid network architecture combining Software-Defined Networking (SDN) and fog computing principles for a resilient underwater submarine landslide-related coastal disaster early warning system. The architecture employs a hierarchical control model, with a centralized SDN controller providing global network management and multiple fog nodes overseeing localized sensor groups. Each sensor node assesses its energy requirements for sending/receiving data before sending information to the local fog controller. Local controllers discover all possible routes and calculating the path energy. Stability analysis, using standard deviation, is performed by the high-level controller to assess and remove paths with fluctuation in energy. The high-level controller uses Z-score and IQR to find outlier routes and filters them out. The high-level controller computes a minimum number of shortest paths to achieve a target reliability. Then, it applies a weighted variance to prioritize critical nodes and Markov chain to define transmission success probability. This integrated approach offers a highly efficient and reliable network by leveraging centralized control with edge intelligence. Simulation results demonstrate that FERDOSI significantly outperforms existing approaches, exhibiting lower latency, reduced packet loss, enhanced throughput, and decreased energy consumption across varying data load conditions, demonstrating the potential to deliver timely data for critical applications.