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With the development of Vehicle Edge Computing (VEC), mobile payment for vehicles has become feasible. However, challenges like the lack of incentive mechanisms for Service Providers (SPs) hinder its widespread adoption. To address this, we propose an incentive mechanism for SPs that operates independently of offloading. Our approach constructs an optimization problem aimed at maximizing the total utility of SPs while meeting users’ basic Quality of Experience (QoE) constraints, considering server latency, energy consumption, and bandwidth costs. We introduce the Soft Actor-Critic based Computational Resource Allocation and Pricing (SCRAP) algorithm to solve this problem. Extensive experiments demonstrate that SCRAP improves SP utility by at least 7.5% compared to existing algorithms, while also ensuring a higher transaction success rate.

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A SAC-Based Incentive Mechanism for Service Provider in Vehicle Edge Computing

  • 会议论文

  • 发表日期：

    2025年

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  • Dun Cao,
  • Shirui Huang,
  • Jiasi Xiong,
  • Jin Wang

摘要

With the development of Vehicle Edge Computing (VEC), mobile payment for vehicles has become feasible. However, challenges like the lack of incentive mechanisms for Service Providers (SPs) hinder its widespread adoption. To address this, we propose an incentive mechanism for SPs that operates independently of offloading. Our approach constructs an optimization problem aimed at maximizing the total utility of SPs while meeting users’ basic Quality of Experience (QoE) constraints, considering server latency, energy consumption, and bandwidth costs. We introduce the Soft Actor-Critic based Computational Resource Allocation and Pricing (SCRAP) algorithm to solve this problem. Extensive experiments demonstrate that SCRAP improves SP utility by at least 7.5% compared to existing algorithms, while also ensuring a higher transaction success rate.