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By deploying mobile edge computing (MEC) at electric vehicle charging stations (CSs), real-time diagnostic analysis of charging fault information can be achieved. To reduce computation delay for the fault information, this study employs data compression before transmission to the MEC server for computing. A joint data compression, decompression, and task offloading problem is formulated to minimize the task offloading delay. Due to the non-convex nature of the problem, we begin by transforming it into a Markov decision process (MDP) framework. To tackle this, a novel joint data compression, decompression, and task offloading (JDCDTO) algorithm is developed based on the Beta-heterogeneous-agent proximal policy optimization (HAPPO) approach. Simulation results indicate that the proposed JDCDTO algorithm achieves superior performance compared to existing benchmark strategies.

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Joint Data Compression, Decompression and Task Offloading for Charging Stations Fault Information Processing

  • 会议论文

  • 发表日期：

    2026年

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  • Guolun Yang,
  • Wenzeng Dou,
  • Rengji Wang,
  • Yilong Wang,
  • Gang Ma,
  • Xiaojiao Xu,
  • Yi Li,
  • Dayu Lin,
  • Liao YingKun

摘要

By deploying mobile edge computing (MEC) at electric vehicle charging stations (CSs), real-time diagnostic analysis of charging fault information can be achieved. To reduce computation delay for the fault information, this study employs data compression before transmission to the MEC server for computing. A joint data compression, decompression, and task offloading problem is formulated to minimize the task offloading delay. Due to the non-convex nature of the problem, we begin by transforming it into a Markov decision process (MDP) framework. To tackle this, a novel joint data compression, decompression, and task offloading (JDCDTO) algorithm is developed based on the Beta-heterogeneous-agent proximal policy optimization (HAPPO) approach. Simulation results indicate that the proposed JDCDTO algorithm achieves superior performance compared to existing benchmark strategies.