Title: FastTrack: Minimizing Stalls for CDN-based Over-the-top Video Streaming Systems,
Abstract: Traffic for internet video streaming has been rapidly increasing and is
further expected to increase with the higher definition videos and IoT
applications, such as 360 degree videos and augmented virtual reality
applications. While efficient management of heterogeneous cloud resources to
optimize the quality of experience is important, existing work in this problem
space often left out important factors. In this paper, we present a model for
describing a today's representative system architecture for video streaming
applications, typically composed of a centralized origin server and several CDN
sites. Our model comprehensively considers the following factors: limited
caching spaces at the CDN sites, allocation of CDN for a video request, choice
of different ports from the CDN, and the central storage and bandwidth
allocation. With the model, we focus on minimizing a performance metric, stall
duration tail probability (SDTP), and present a novel, yet efficient, algorithm
to solve the formulated optimization problem. The theoretical bounds with
respect to the SDTP metric are also analyzed and presented. Our extensive
simulation results demonstrate that the proposed algorithms can significantly
improve the SDTP metric, compared to the baseline strategies. Small-scale video
streaming system implementation in a real cloud environment further validates
our results.