Publication | Closed Access
QoE-Aware Computing Resource Allocation for CDN-as-a-Service Provision
14
Citations
12
References
2016
Year
Unknown Venue
EngineeringDynamic Resource AllocationEdge ComputingCdn-as-a-service ProvisionVirtualized Video ServiceCloud ComputingVirtual RealityCdnaas InstanceBusinessQuality-of-serviceQoe AssessmentMobile ComputingComputer ScienceMultimedia DeliveryVideo DistributionContent Delivery Network
We focus on the provision of Content-Delivery-Network-as-a- Service (CDNaaS) functionality for video distribution and, in particular, on how to appropriately decide on the amount of computing resources to allocate to a CDNaaS instance to satisfy Quality of Experience (QoE) and resource capacity constraints. Our work is put in the context of a telco cloud environment, which is open for content providers to request the dynamic deployment of a virtual CDN infrastructure on top of it, to cover a target user demand with a desired service quality at the regions where the telecom operator has presence. We perform extensive testbed experiments to quantify the dependence of user experience on the load of a virtualized video service, and apply our measurement results to drive a QoE-aware virtual CPU resource allocation algorithm. Using simulation, we show our algorithm to optimally address the quality-cost tradeoff, demonstrating the benefits of QoE-awareness.
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