From Theory to Practice: Improving Bitrate Adaptation in the DASH Reference Player
From Theory to Practice: Improving Bitrate Adaptation in the DASH Reference Player
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DOI：
10.1145/3336497
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发表时间：
2019-08-01
影响因子：
5.1
通讯作者：
Sparacio, Daniel
中科院分区：
文献类型：
--
作者：
Spiteri, Kevin;Sitaraman, Ramesh;Sparacio, Daniel
现代视频流使用自适应比特率（ABR）算法，该算法在视频播放器内运行并不断调整质量（即，比特率）。为了最大化用户的体验质量（QoE），ABR算法必须以具有低再缓冲和低比特率振荡的高比特率进行流传输。此外，良好的ABR算法对用户和网络事件做出响应，并且可以用于要求苛刻的场景，例如低延迟直播流。最近的研究论文提供了丰富的ABR算法，但不符合上述许多现实世界的需求。我们开发Sabre，一个开源的公开可用的模拟工具，使自适应流媒体环境的快速和准确的模拟。我们对Sabre进行了经验验证，以证明它准确地模拟了现实世界的环境。我们使用Sabre设计和评估BOLA-E和DYNAMIC，两个新的ABR算法。我们还开发了一种快速重传算法，可以用更高比特率（因此更高质量）的片段替换已经下载的片段。新算法在更高的比特率、更少的重新缓冲和更少的比特率振荡方面为用户提供更高的QoE。此外，这些算法对用户事件（如启动和查找）的反应更快，对网络事件（如吞吐量的提高）的反应也更快。此外，它们对于需要低延迟的直播流表现得非常好，这对于ABR算法来说是一个具有挑战性的场景。总体而言，与最先进的算法相比，我们的算法为现实生活中的自适应视频流提供了上级视频QoE和响应能力。重要的是，本文中介绍的所有三种算法现在都是官方DASH参考播放器dash的一部分。视频提供商正在生产环境中使用。虽然我们的评估和实现集中在DASH环境中，但我们的算法同样适用于其他自适应流媒体格式，如Apple HLS。
Modern video streaming uses adaptive bitrate (ABR) algorithms that run inside video players and continually adjust the quality (i.e., bitrate) of the video segments that are downloaded and rendered to the user. To maximize the quality-of-experience (QoE) of the user, ABR algorithms must stream at a high bitrate with low rebuffering and low bitrate oscillations. Further, a good ABR algorithm is responsive to user and network events and can be used in demanding scenarios such as low-latency live streaming. Recent research papers provide an abundance of ABR algorithms but fall short on many of the above real-world requirements.We develop Sabre, an open-source publicly available simulation tool that enables fast and accurate simulation of adaptive streaming environments. We empirically validated Sabre to show that it accurately simulates real-world environments. We used Sabre to design and evaluate BOLA-E and DYNAMIC, two novel ABR algorithms. We also developed a FAST SWITCHING algorithm that can replace segments that have already been downloaded with higher-bitrate (thus, higher-quality) segments. The new algorithms provide higher QoE to the user in terms of higher bitrate, fewer rebuffers, and lesser bitrate oscillations. In addition, these algorithms react faster to user events such as startup and seek, and they respond more quickly to network events such as improvements in throughput. Further, they perform very well for live streams that require low latency, a challenging scenario for ABR algorithms. Overall, our algorithms offer superior video QoE and responsiveness for real-life adaptive video streaming, in comparison to the state-of-the-art. Importantly, all three algorithms presented in this article are now part of the official DASH reference player dash. is and are being used by video providers in production environments. While our evaluation and implementation are focused on the DASH environment, our algorithms are equally applicable to other adaptive streaming formats such as Apple HLS.