An Analysis of Delay in Live 360° Video Streaming Systems
An Analysis of Delay in Live 360° Video Streaming Systems
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DOI：
10.1145/3394171.3413539
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发表时间：
2020-10
期刊：
影响因子：
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通讯作者：
Jun Yi;Md Reazul Islam;Shivang Aggarwal;Dimitrios Koutsonikolas;Y. Charlie Hu;Zhisheng Yan
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文献类型：
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作者：
Jun Yi;Md Reazul Islam;Shivang Aggarwal;Dimitrios Koutsonikolas;Y. Charlie Hu;Zhisheng Yan
虽然实时360°视频流提供了丰富的观看体验，但保证用户体验免受由启动延迟、事件到眼睛延迟和低帧速率引入的负面影响是具有挑战性的。因此，必须了解实时360°流媒体系统的不同计算任务如何影响这三个延迟度量。虽然之前的工作已经研究了商业直播360°视频流系统，但没有一个深入到端到端的管道，并探讨任务级的时间消耗如何影响用户体验。在本文中，我们对实时360°视频流中的五个系统组件的任务级时间消耗进行了首次深入的测量研究。我们首先确定的微妙关系之间的时间消耗故障整个系统管道和三个延迟度量。然后，我们建立了一个原型宙斯来衡量这种关系。我们的研究结果表明了摄像机和服务器初始化时CPU-GPU传输的重要性，以及360°视频拼接对延迟指标的影响可以忽略不计。我们最后验证，我们的结果是代表真实的世界的系统，通过比较他们与商业系统。
While live 360° video streaming provides an enriched viewing experience, it is challenging to guarantee the user experience against the negative effects introduced by start-up delay, event-to-eye delay, and low frame rate. It is therefore imperative to understand how different computing tasks of a live 360° streaming system contribute to these three delay metrics. Although prior works have studied commercial live 360° video streaming systems, none of them has dug into the end-to-end pipeline and explored how the task-level time consumption affects the user experience. In this paper, we conduct the first in-depth measurement study of task-level time consumption for five system components in live 360° video streaming. We first identify the subtle relationship between the time consumption breakdown across the system pipeline and the three delay metrics. We then build a prototype Zeus to measure this relationship. Our findings indicate the importance of CPU-GPU transfer at the camera and the server initialization as well as the negligible effect of 360° video stitching on the delay metrics. We finally validate that our results are representative of real world systems by comparing them with those obtained with a commercial system.