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Traffic for internet video streaming has been rapidly increasing and isfurther expected to increase with the higher definition videos and IoTapplications, such as 360 degree videos and augmented virtual realityapplications. While efficient management of heterogeneous cloud resources tooptimize the quality of experience is important, existing work in this problemspace often left out important factors. In this paper, we present a model fordescribing a today's representative system architecture for video streamingapplications, typically composed of a centralized origin server and several CDNsites. Our model comprehensively considers the following factors: limitedcaching spaces at the CDN sites, allocation of CDN for a video request, choiceof different ports from the CDN, and the central storage and bandwidthallocation. With the model, we focus on minimizing a performance metric, stallduration tail probability (SDTP), and present a novel, yet efficient, algorithmto solve the formulated optimization problem. The theoretical bounds withrespect to the SDTP metric are also analyzed and presented. Our extensivesimulation results demonstrate that the proposed algorithms can significantlyimprove the SDTP metric, compared to the baseline strategies. Small-scale videostreaming system implementation in a real cloud environment further validatesour results.

FastTrack: Minimizing Stalls for CDN-based Over-the-top Video Streaming Systems