可扩展视频流的多层主动队列管理和拥塞控制

Seong-ryong Kang, Yueping Zhang, Min Dai, D. Loguinov
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引用次数: 24

摘要

视频流正在成为当今互联网日益重要的一部分。为了保证最终用户获得高质量的流媒体环境,许多视频应用需要严格的网络QoS,而这在当前的Internet中是无法实现的。因此,为了补充现有网络的尽力而为模型,我们研究了一种新的视频流框架,该框架允许应用程序用不同的优先级标记自己的数据包,并在路由器内部使用多队列拥塞控制,以便在缓冲区溢出时有效地丢弃不太重要的数据包。我们描述了在任意网络丢失情况下为视频应用提供“最佳”性能的优先级AQM算法,并结合我们的框架研究了Kelly拥塞控制的一种变体。我们称这种组合架构为PELS——分区增强层流。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-layer active queue management and congestion control for scalable video streaming
Video streaming is becoming an increasingly important part of the present Internet. To guarantee a high-quality streaming environment to end users, many video applications require a strict form of network QoS that is not available in the present Internet. Thus, to supplement the best-effort model of existing networks, we study a new video streaming framework that allows applications to mark their own packets with different priority and use multiqueue congestion control inside routers to effectively drop the less-important packets during buffer overflows. We describe priority AQM algorithms that provide "optimal" performance to video applications under arbitrary network loss and study a variation of Kelly's congestion control in combination with our framework. We call the combined architecture PELS - partitioned enhancement layer streaming.
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