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This paper proposes and evaluates a novel algorithm for streaming video overHTTP. The problem is formulated as a non-convex optimization problem which isconstrained by the predicted available bandwidth, chunk deadlines, availablevideo rates, and buffer occupancy. The objective is to optimize a QoE metricthat maintains a tradeoff between maximizing the playback rate of every chunkand ensuring fairness among different chunks for the minimum re-buffering time.We propose FastScan, a low complexity algorithm that solves the problem. Onlineadaptations for dynamic bandwidth environments are proposed with imperfectavailable bandwidth prediction. Results of experiments driven by Variable BitRate (VBR) encoded video, video platform system (dash.js), and cellularbandwidth traces of a public dataset reveal the robustness of the onlineversion of FastScan algorithm and demonstrate its significant performanceimprovement as compared to the considered state-of-the-art video streamingalgorithms. For example, on an experiment conducted over 100 real cellularavailable bandwidth traces of a public dataset that spans different availablebandwidth regimes, our proposed algorithm (FastScan) achieves the minimumre-buffering (stall) time and the maximum average playback rate in every singletrace as compared to Bola, Festive, BBA, RB, and FastMPC, and Pensievealgorithms.

FastScan: Robust Low-Complexity Rate Adaptation Algorithm for Video Streaming over HTTP