DQ-DASH
DQ-DASH
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DOI：
10.1145/3371040
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发表时间：
2020-03
期刊：
影响因子：
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通讯作者：
A. Bentaleb;P. Yadav;Wei Tsang Ooi;Roger Zimmermann
中科院分区：
文献类型：
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作者：
A. Bentaleb;P. Yadav;Wei Tsang Ooi;Roger Zimmermann
HTTP自适应视频流传输（HAS）（诸如HTTP上的动态自适应流传输（DASH））在互联网上的显著普及已经导致用户在视频质量和递送鲁棒性方面的期望的显著增加。这种情况给内容提供商带来了新的挑战，内容提供商必须通过尽力而为的网络基础设施满足其客户的体验质量（QoE）要求和需求。与传统的单服务器DASH不同，我们开发了一种用于DASH的分布式DASH理论比特率自适应算法（DQ-DASH），该算法通过并行下载片段来利用多个服务器的可用性。DQ-DASH使用基于Mx/D/1/K排队理论的比特率选择，结合请求调度器，通过并行请求下载相同质量的后续片段，以减少质量波动。DQ-DASH有助于聚合来自不同服务器的带宽，并通过路径多样性提高容错性和鲁棒性。由此产生的弹性防止客户端在一些服务器变得拥塞时遭受QoE降级。DQ-DASH还有助于充分利用来自服务器的聚合带宽，并以最高的吞吐量从服务器下载迫切需要的片段。我们还分析了多源视频流的缓冲区容量和段持续时间的影响。
The significant popularity of HTTP adaptive video streaming (HAS), such as Dynamic Adaptive Streaming over HTTP (DASH), over the Internet has led to a stark increase in user expectations in terms of video quality and delivery robustness. This situation creates new challenges for content providers who must satisfy the Quality-of-Experience (QoE) requirements and demands of their customers over a best-effort network infrastructure. Unlike traditional single server DASH, we developed a Distributed Queuing theory bitrate adaptation algorithm for DASH (DQ-DASH) that leverages the availability of multiple servers by downloading segments in parallel. DQ-DASH uses a Mx/D/1/K queuing theory based bitrate selection in conjunction with the request scheduler to download subsequent segments of the same quality through parallel requests to reduce quality fluctuations. DQ-DASH facilitates the aggregation of bandwidth from different servers and increases fault-tolerance and robustness through path diversity. The resulting resilience prevents clients from suffering QoE degradations when some of the servers become congested. DQ-DASH also helps to fully utilize the aggregate bandwidth from the servers and download the imminently required segment from the server with the highest throughput. We have also analyzed the effect of buffer capacity and segment duration for multi-source video streaming.