Resource Sharing among Edge Service Providers: Modeling and Solution

• Main Authors: Zhu, Renqi, Lin, Xiang, Wu, Shoujiang, Fu, Wenxuan, Luo, Lailong, Zhang, Boquan
• Format: Conference Proceeding
• Language: English
• Subjects: Computational modeling; Costs; Data models; Data processing; Edge computing; Low latency communication; Modeling; Resource management; Resource sharing
• ISSN: 2771-6902
• DOI: 10.1109/BigDIA60676.2023.10429529

The basic idea of edge computing is to provide cloud computing capability and IT service environment for application developers and content providers at the network edge close to terminal devices, thus creating a big data processing service environment with high performance, low latency, and high bandwidth. Researchers have proposed an edge federation resource management and service distribution architecture based on dynamic resource configuration, enabling independent edge computing facilities and cloud data centers to seamlessly achieve resource collaboration and service response, and effectively schedule and utilize resources in multiple edge infrastructure providers (EIPs). Service distribution based on edge federation architecture can effectively reduce the overall cost of EIP and improve the level of service distribution. However, the social welfare of each participant in Edge Federation has not been quantified and optimized, and the incentive mechanism for members to participate in the federation is not yet clear. Therefore, the purpose of this study is to build an edge service provider (ESP) federation, enable cross-EIP user request processing mechanism, realize resource sharing among multiple edge infrastructure providers, comprehensively analyze the benefits and costs of all participants in edge computing, and maximize the social welfare of all members. In addition, we optimize the latency of user request processing, improve the efficiency of user request processing, and enhance user satisfaction.