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.
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Tasiopoulos et al. (2018) studied this question.
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