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<p>This paper addresses the allocation and pricing problem of device-to-device (D2D) computing power resources in end-side networks and proposes a platform-assisted pricing-and-matching configuration model based on a two-sided market game. The model explicitly considers three types of participants: service users (SUs), requesting users (RUs), and the operator platform. In the proposed framework, SUs provide idle computing resources, RUs purchase computing resources for task offloading, and the platform collects supply–demand information, sets the commission rate, organizes stable matching, and supports SU-RU transaction negotiation. An integrated solution algorithm combining commission-rate search, Gale-Shapley stable matching, and Nash bargaining is developed to obtain feasible matching relationships, transaction prices, and resource allocation decisions. Simulation results show that the commission rate significantly affects platform revenue, SU net profit, RU utility, and transaction participation. A higher commission rate increases the platform share of each transaction but may reduce the willingness of SUs and RUs to participate, thereby creating a trade-off between platform profit and market attractiveness. The proposed model provides a theoretical basis for platform pricing regulation and D2D-assisted computing resource trading in end-side networks.</p>

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Research on end-side network computing power pricing and matching mechanism based on two-sided market game

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月14日

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  • Yajing Wang,
  • Xianglong Meng,
  • Lei Zhang,
  • Ming Chen,
  • Wei Liu,
  • Peng Lin

摘要

This paper addresses the allocation and pricing problem of device-to-device (D2D) computing power resources in end-side networks and proposes a platform-assisted pricing-and-matching configuration model based on a two-sided market game. The model explicitly considers three types of participants: service users (SUs), requesting users (RUs), and the operator platform. In the proposed framework, SUs provide idle computing resources, RUs purchase computing resources for task offloading, and the platform collects supply–demand information, sets the commission rate, organizes stable matching, and supports SU-RU transaction negotiation. An integrated solution algorithm combining commission-rate search, Gale-Shapley stable matching, and Nash bargaining is developed to obtain feasible matching relationships, transaction prices, and resource allocation decisions. Simulation results show that the commission rate significantly affects platform revenue, SU net profit, RU utility, and transaction participation. A higher commission rate increases the platform share of each transaction but may reduce the willingness of SUs and RUs to participate, thereby creating a trade-off between platform profit and market attractiveness. The proposed model provides a theoretical basis for platform pricing regulation and D2D-assisted computing resource trading in end-side networks.