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ARBITER: Adaptive rate-based intelligent HTTP streaming algorithm

机译:arbiter:基于自适应速率的智能HTTP流算法

摘要

Dynamic Adaptive streaming over HTTP (DASH) is widely used by content providers for video delivery and dominates traffic on cellular networks. The inherent variability in both video bitrate and network bandwidth negatively impacts the user Quality of Experience (QoE), motivating the design of better DASH-compliant adaptation algorithms. In this paper we present ARBITER, a novel streaming adaptation algorithm that explicitly integrates the variations in both video and network dynamics in its adaptation decisions. Our simulation-based performance evaluation, using real video content and cellular bandwidth traces, shows that ARBITER achieves an excellent tradeoff among streaming metrics in terms of received video quality, stall count, stall duration, and switching dynamics, leading to a relative improvement of 17-45% in user QoE in comparison to state-of-the-art algorithms.
机译:内容提供商广泛使用HTTP动态自适应流式传输(DASH)进行视频传输,并支配了蜂窝网络上的流量。视频比特率和网络带宽的固有可变性会对用户的体验质量(QoE)产生负面影响,从而促使人们设计出更好的DASH兼容自适应算法。在本文中,我们提出了一种新颖的流媒体自适应算法ARBITER,该算法在其自适应决策中明确集成了视频和网络动态变化。我们使用真实视频内容和蜂窝带宽轨迹进行的基于仿真的性能评估表明,ARBITER在接收视频质量,停顿计数,停顿持续时间和切换动态方面,在流媒体指标之间实现了极佳的权衡,相对改善了17与最新算法相比,用户QoE达到-45%。

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