Mobile edge computing seeks to provide resources to different delay-sensitive applications. This is a challenging problem as an edge cloud-service provider may not have sufficient resources to satisfy all resource requests. Furthermore, allocating available resources optimally to different applications is also challenging. Resource sharing among different edge cloud-service providers can address the aforementioned limitation as certain service providers may have resources available that can be ``rented'' by other service providers. However, edge cloud service providers can have different objectives or \emph{utilities}. Therefore, there is a need for an efficient and effective mechanism to share resources among service providers, while considering the different objectives of various providers. We model resource sharing as a multi-objective optimization problem and present a solution framework based on \emph{Cooperative Game Theory} (CGT). We consider the strategy where each service provider allocates resources to its native applications first and shares the remaining resources with applications from other service providers. We prove that for a monotonic, non-decreasing utility function, the game is canonical and convex. Hence, the \emph{core} is not empty and the grand coalition is stable. We propose two algorithms \emph{Game-theoretic Pareto optimal allocation} (GPOA) and \emph{Polyandrous-Polygamous Matching based Pareto Optimal Allocation} (PPMPOA) that provide allocations from the core. Hence the obtained allocations are \emph{Pareto} optimal and the grand coalition of all the service providers is stable. Experimental results confirm that our proposed resource sharing framework improves utilities of edge cloud-service providers and application request satisfaction.

中文翻译：

---

让我们分享：移动边缘云中资源共享的博弈论框架

移动边缘计算旨在为不同的延迟敏感应用程序提供资源。这是一个具有挑战性的问题，因为边缘云服务提供商可能没有足够的资源来满足所有资源请求。此外，将可用资源最佳地分配给不同的应用程序也具有挑战性。不同边缘云服务提供商之间的资源共享可以解决上述限制，因为某些服务提供商可能拥有可供其他服务提供商“租用”的资源。但是，边缘云服务提供商可能有不同的目标或 \emph{utilities}。因此，需要一种高效且有效的机制来在服务提供商之间共享资源，同时考虑到各个提供商的不同目标。我们将资源共享建模为一个多目标优化问题，并提出了一个基于\emph{合作博弈论}（CGT）的解决方案框架。我们考虑的策略是每个服务提供商首先将资源分配给其本地应用程序，然后与其他服务提供商的应用程序共享剩余资源。我们证明，对于单调的、非递减的效用函数，博弈是规范的和凸的。因此，\emph{core} 不是空的，大联盟是稳定的。我们提出了两种算法\emph{博弈论帕累托最优分配}（GPOA）和\emph{基于Polyandrous-Polygamous匹配的帕累托最优分配}（PPMPOA），它们提供来自核心的分配。因此，获得的分配是 \emph {Pareto} 最优的，并且所有服务提供商的大联盟是稳定的。