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.

翻译：我们针对dash.js动态自适应流媒体（DASH）播放器中三种自适应比特率（ABR）算法在多种延迟目标和配置选项下的低延迟性能进行了分析。实验在我们的DASH测试平台上进行，该平台支持使用一系列真实网络配置进行测试。我们的实验有助于深入理解延迟目标如何影响体验质量（QoE），以及不同算法在达成目标方面的表现差异。研究发现，在dash.js v4.5.0版本中，默认的动态算法实现了最优的整体QoE。结果表明，虽然其他算法能在较低延迟下获得更高视频质量，但这是以增加卡顿为代价的。我们分析了L2A-LL算法在测试中的不佳表现，并提出了能显著提升性能的改进方案。此外，我们还指出部分低延迟配置设置可能对性能产生负面影响。