直播场景下CMAF的评估

Tomasz Lyko, M. Broadbent, N. Race, M. Nilsson, Paul Farrow, S. Appleby
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引用次数: 4

摘要

HTTP自适应流(HAS)技术,如MPEG DASH,现在广泛用于向大量观众提供电视服务。在HAS中,客户端使用HTTP请求内容片段,ABR算法选择请求每个片段的质量,以权衡视频质量并避免延迟。与传统广播相比,这带来了显著的端到端延迟,因为客户端需要足够大的缓冲区,以便ABR算法及时对网络条件的变化做出反应。最近标准化的通用媒体应用程序格式(CMAF)通过将段定义为由独立可传输的块组成,帮助解决了延迟问题。在本文中,我们描述了一个我们开发的仿真模型,用于评估四种流行的ABR算法在各种低延迟直播场景下使用DASH和CMAF的性能。评估使用了实际的网络条件,这些条件基于从商业电视直播服务的CDN日志中获取的吞吐量数据。我们使用选择的QoE指标量化ABR算法的性能,并表明CMAF可以显着提高低延迟场景下的ABR性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of CMAF in live streaming scenarios
HTTP Adaptive Streaming (HAS) technologies such as MPEG DASH are now used extensively to deliver television services to large numbers of viewers. In HAS, the client requests segments of content using HTTP, with an ABR algorithm selecting the quality at which to request each segment to trade-off video quality with the avoidance of stalling. This introduces significant end to end latency compared to traditional broadcast, due to the the client requiring a large enough buffer for the ABR algorithm to react to changes in network conditions in a timely manner. The recently standardised Common Media Application Format (CMAF) has helped address the issue of latency by defining segments as composed of independently transferable chunks. In this paper, we describe a simulation model we have developed to evaluate the performance of four popular ABR algorithms using DASH and CMAF in various low latency live streaming scenarios. Realistic network conditions are used for the evaluation, which are based on throughput data taken from the CDN logs of a commercial live TV service. We quantify the performance of the ABR algorithms using a selection of QoE metrics, and show that CMAF can significantly improve ABR performance in low delay scenarios.
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