Optimal Strategies for Live Video Streaming in the Low-latency Regime
Optimal Strategies for Live Video Streaming in the Low-latency Regime
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DOI：
10.1109/icnp.2019.8888127
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发表时间：
2019-10
期刊：
影响因子：
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通讯作者：
Liyang Sun;Tongyu Zong;Yong Liu;Yao Wang;Haihong Zhu
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文献类型：
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作者：
Liyang Sun;Tongyu Zong;Yong Liu;Yao Wang;Haihong Zhu
低延迟是直播视频流的关键用户体验质量（QoE）指标。这对通过互联网进行流媒体传输提出了重大挑战。在本文中，我们探索低延迟实时视频流的设计空间，通过开发动态模型和最优控制策略。我们在模型预测控制（MPC）框架内进一步开发实用的实时视频流算法，即MPC-Live，以通过调整视频比特率来最大化用户QoE，同时在动态网络环境中保持较低的端到端视频延迟。通过大量的实验驱动的真实的网络痕迹，我们证明，我们的实时视频流算法可以显着提高性能的延迟范围内2至5秒。
Low-latency is a critical user Quality-of-Experience (QoE) metric for live video streaming. It poses significant challenges for streaming over the Internet. In this paper, we explore the design space of low-latency live video streaming by developing dynamic models and optimal control strategies. We further develop practical live video streaming algorithms within the Model Predictive Control (MPC) framework, namely MPC-Live, to maximize user QoE by adapting the video bitrate while maintaining low end-to-end video latency in dynamic network environment. Through extensive experiments driven by real network traces, we demonstrate that our live video streaming algorithms can improve the performance dramatically within latency range of two to five seconds.