Existing works adopt the Edge-Oriented Resource Allocation (EORA) scheme, in which edge nodes cache services and schedule user requests to distribute workloads over cloud and edge nodes, so as to achieve high-quality services and low latency. Unfortunately, EORA does not fully take into account the fact that service providers are sometimes independent from the edge operators with their own objectives. To deal with the conflict and cooperation between service providers and edge nodes, we devise a service-oriented resource allocation (SORA) scheme, where edge nodes and service providers adjust their resource allocations to provide requested services. We first prove that such resource allocation problem is NP-hard. We then propose a three-sided cyclic game (3CG) involving users, edge nodes, and service providers who make their individual decisions by choosing respectively high-quality services, high-value users, and cost-effective edge nodes for service deployment. Based on 3CG, we prove the existence and approximation ratio of pure-strategy Nash equilibriums (NEs). We also develop both centralized and distributed approximate algorithms for resource allocation. Finally, extensive experimental results validate the effectiveness and convergence of the proposed algorithms.

中文翻译：

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边缘计算中面向服务的资源分配的循环博弈

现有工作采用面向边缘的资源分配（EORA）方案，其中边缘节点缓存服务并调度用户请求将工作负载分配到云和边缘节点，从而实现高质量服务和低延迟。不幸的是，EORA 并没有充分考虑到服务提供商有时独立于边缘运营商并拥有自己的目标这一事实。为了处理服务提供商和边缘节点之间的冲突和合作，我们设计了面向服务的资源分配（SORA）方案，其中边缘节点和服务提供商调整他们的资源分配以提供请求的服务。我们首先证明这种资源分配问题是 NP-hard 问题。然后我们提出了一个三边循环博弈（3CG），涉及用户、边缘节点、和服务提供商通过分别选择高质量的服务、高价值的用户和具有成本效益的边缘节点来进行服务部署，从而做出各自的决策。基于3CG，我们证明了纯策略纳什均衡（NEs）的存在性和逼近率。我们还开发了用于资源分配的集中式和分布式近似算法。最后，大量的实验结果验证了所提出算法的有效性和收敛性。