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    ARTICLE

    A Task Offloading Strategy Based on Multi-Agent Deep Reinforcement Learning for Offshore Wind Farm Scenarios

    Zeshuang Song1, Xiao Wang1,*, Qing Wu1, Yanting Tao1, Linghua Xu1, Yaohua Yin2, Jianguo Yan3

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 985-1008, 2024, DOI:10.32604/cmc.2024.055614 - 15 October 2024

    Abstract This research is the first application of Unmanned Aerial Vehicles (UAVs) equipped with Multi-access Edge Computing (MEC) servers to offshore wind farms, providing a new task offloading solution to address the challenge of scarce edge servers in offshore wind farms. The proposed strategy is to offload the computational tasks in this scenario to other MEC servers and compute them proportionally, which effectively reduces the computational pressure on local MEC servers when wind turbine data are abnormal. Finally, the task offloading problem is modeled as a multi-intelligent deep reinforcement learning problem, and a task offloading model… More >

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