Browsing by Author "James, Cyriac"

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    Improving Quality of Experience (QoE) of Dynamic Adaptive Streaming (DAS) Systems
    (2019-09-19) James, Cyriac; Wang, Mea; Krishnamurthy, Diwakar; Williamson, Carey L.; Alim, Usman R.; Liu, Yang
    Dynamic Adaptive Streaming (DAS) systems dominate today's video streaming over the Internet, and operate by adapting video quality based on network throughput variation using discrete quality levels. Despite their popularity, it lacks an effective adaptation that minimizes stalls and quality switches while maximizing visual quality, especially when available bandwidth varies. The conventional approach to adaptation is to make a decision on the next video segment quality based on prior throughput measurements. This approach is not robust to bandwidth fluctuation at small time scales, which can consequently lead to stalls, bandwidth waste, and unstable quality, mainly due to the inability to mitigate significant bandwidth reduction during the segment download. MultiPath TCP (MPTCP) is an emerging paradigm that could offer significant benefits to video streaming by harnessing bandwidth from multiple network interfaces, in particular on mobile and desktop devices with support for both WiFi and cellular networks. We first investigate this off-the-shelf solution to improve video streaming performance by harvesting additional bandwidth over always or intermittently available secondary link under different bandwidth variability conditions. Our measurement study yields mixed results. While beneficial to user experience when primary link bandwidth is unstable or constrained, MPTCP may not offer any advantage otherwise, and sometimes could be detrimental. We then propose BETA – Bandwidth-Efficient Temporal Adaptation, an agile approach that allows DAS players to refine the quality level within video segments on the fly, according to the actual bandwidth conditions experienced while downloading each segment. We define a new DAS-oriented transmission order of video frames within segments that facilitates decodability of partial frames, and paves the way for changing the paradigm from discrete to continuous bitrate ladders for DAS. BETA can work with any adaptation algorithm that runs on a DAS player to significantly improve robustness and efficiency in dynamic network environments and for low-latency streams, as well as dramatically reduce content storage and encoding infrastructure requirements.