2018 · 11 citations · 9 references
ComputingCloud ComputingComputer ScienceCloud InfrastructureDistributed SystemsEdge ComputingEdge Computing InfrastructureEdge InfrastructureEdge-cloud ArchitectureResource ProvisioningResource SchedulingTask OffloadingCloud-edge OffloadingDesign PrinciplesDistributed CloudDistributed Edge InfrastructureEdge OffloadingService OffloadingService PlacementWorkload Offloading
New bandwidth-intensive and time-constrained services in 5G networks combined with network function virtualization is pushing network operators to deploy distributed cloud infrastructures at the edge of the network. Allocating resources in capacity-limited infrastructures raises new challenges, which have not really been so far considered in the cloud literature. In this context, we investigate placement and offloading strategies of constrained services. We set design principles of future distributed edge clouds in order to meet application requirements. We precisely introduce a costless distributed resource allocation algorithm, named CLOSE, which considers local information only. We compare via simulations the performance of CLOSE against those obtained by using mechanisms proposed in the literature, notably the Tricircle project within OpenStack. It turns out that the proposed distributed algorithm yields better performance while requiring less overhead.
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