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Edge-MAP: Auction Markets for Edge Resource Provisioning

机译:Edge-MAP:边缘资源供应的拍卖市场

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New and emerging applications in the entertainment (e.g., Virtual/Augmented Reality), IoT and automotive domains will soon demand response times an order of magnitude smaller than can be achieved by the current “client-to-cloud” network model. Edge-and Fog-computing have been proposed as the promise to deal with such extremely latency-sensitive applications. According to Edge-/Fog-Computing, computing resources are available at the edge of the network for applications to run their virtualised instances. We assume a distributed computing environment, where In-Network Computing Providers (IN CPs) deploy and lease edge resources, while Application Service Providers (AppSPs) have the opportunity to rent those resources to meet their application's latency demands. We build an auction-based resource allocation and provisioning mechanism which produces a map of application instances in the edge computing infrastructure (hence, acronymed Edge-MAP). Edge-MAP takes into account users' mobility (i.e., users connecting to different cell stations over time) and the limited computing resources available in edge micro-clouds to allocate resources to bidding applications. On the micro-level, Edge-MAP relies on Vickrey-English-Dutch (VED) auctions to perform robust resource allocation, while on the macro-level it fosters competition among neighbouring IN CPs. In contrast to related studies in the area, Edge-MAP can scale to any number of applications, adapt to dynamic network conditions rapidly and reallocate resources in polynomial time. Our evaluation demonstrates Edge-MAP's capability of taking into account the inherent challenges of the provisioning problem we consider.
机译:娱乐(例如虚拟/增强现实),物联网和汽车领域中的新兴应用将很快需要比当前“客户端到云”网络模型可实现的响应时间短一个数量级的响应时间。边缘和雾计算已被提议作为应对此类对延迟特别敏感的应用程序的承诺。根据边缘/雾计算,网络边缘上的计算资源可供应用程序运行其虚拟化实例。我们假设一个分布式计算环境,其中网络内计算提供程序(IN CP)部署和租用边缘资源,而应用程序服务提供程序(AppSP)则有机会租用这些资源以满足其应用程序的延迟需求。我们建立了一个基于拍卖的资源分配和供应机制,该机制可在边缘计算基础架构(因此,简称为Edge-MAP)中生成应用程序实例的地图。 Edge-MAP考虑了用户的移动性(即,用户随时间连接到不同的基站)和边缘微云中可用的有限计算资源,无法将资源分配给竞标应用程序。在微观层次上,Edge-MAP依靠Vickrey-English-Dutch(VED)拍卖来执行可靠的资源分配,而在宏观层次上,它促进了相邻IN CP之间的竞争。与该领域的相关研究相比,Edge-MAP可以扩展到任意数量的应用程序,可以快速适应动态网络条件并在多项式时间内重新分配资源。我们的评估证明了Edge-MAP能够考虑到我们所考虑的置备问题所固有的挑战。

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