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Adaptive rate control for streaming stored fine-grained scalable video

机译:流媒体储存细粒度可伸缩视频的自适应速率控制

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In this paper we investigate adaptive streaming of stored fine-grained scalable video over a TCP-friendly connection. The goal is to develop low-complexity yet high-performing schemes that adequately adapt to the short- and long-term variations in available bandwidth. We first present a novel framework for low-complexity streaming of fine-grained scalable video over a TCP-friendly connection. In the context of this scheme, and under the assumption of complete knowledge of bandwidth evolution, we derive an optimal policy for a criterion that involves both image quality and quality variability during playback. Based on this ideal optimal policy, we develop a real-time heuristic to stream fine-grained scalable video over the Internet, and we study its performance using real Internet traces. We find that our heuristic policy performs almost as well as the ideal optimal policy for a wide-range of bandwidth scenarios and when run over ordinary TCP the policy is essentially as good as when running the policy over popular TCP-friendly algorithms.
机译:在本文中,我们研究了通过TCP友好的连接调查了存储的细粒度可扩展视频的自适应流。目标是开发出低复杂性但高性能的计划,以充分适应可用带宽的短期和长期变化。我们首先在TCP友好的连接上介绍了一种用于细粒度可扩展视频的低复杂性流媒体的新框架。在该方案的上下文中,在播放涉及在播放期间的图像质量和质量变化的标准,我们推导了最佳政策。基于这一理想的最佳政策,我们开发了一个实时启发式,通过互联网将细粒度可扩展的视频流流,我们使用真正的互联网迹线研究其性能。我们发现我们的启发式政策几乎表现出了广泛的带宽场景以及在普通的TCP上运行时,该策略与在流行的TCP友好算法上运行策略时,策略基本上如此好。

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