Latency Target based Analysis of the DASH.js Player

P. O'Hanlon, Adil Aslam
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Abstract

We analyse the low latency performance of the three Adaptive Bitrate (ABR) algorithms in the dash.js Dynamic Adaptive Streaming over HTTP (DASH) player with respect to a range of latency targets and configuration options. We perform experiments on our DASH Testbed which allows for testing with a range of real world derived network profiles. Our experiments enable a better understanding of how latency targets affect quality of experience (QoE), and how well the different algorithms adhere to their targets. We find that with dash.js v4.5.0 the default Dynamic algorithm achieves the best overall QoE. We show that whilst the other algorithms can achieve higher video quality at lower latencies, they do so only at the expense of increased stalling. We analyse the poor performance of L2A-LL in our tests and develop modifications which demonstrate significant improvements. We also highlight how some low latency configuration settings can be detrimental to performance.
基于延迟目标的DASH.js播放器分析
我们根据一系列延迟目标和配置选项分析了DASH .js动态自适应HTTP流(DASH)播放器中三种自适应比特率(ABR)算法的低延迟性能。我们在DASH测试台上进行实验,该测试台允许使用一系列真实世界衍生的网络配置文件进行测试。我们的实验能够更好地理解延迟目标如何影响体验质量(QoE),以及不同算法如何坚持其目标。我们发现,在dash.js v4.5.0中,默认的动态算法实现了最佳的总体QoE。我们表明,虽然其他算法可以在更低的延迟下实现更高的视频质量,但它们这样做只是以增加延迟为代价。我们在测试中分析了L2A-LL的不良性能,并进行了改进,结果显示有显著改善。我们还强调了一些低延迟配置设置如何损害性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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