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An Analysis of Delay in Live 360° Video Streaming Systems

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Published:12 October 2020Publication History

ABSTRACT

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.

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Supplemental Material

3394171.3413539.mp4

In this presentation, we?ll show an analysis of delay in 360° live video streaming systems. The goal of this presentation will be fourfold. First, we?ll dissect three main delay metrics that affect user experience: the start-up delay, event-to-eye delay and the frame rate. During this time, we?ll show what the system pipeline tasks are that contribute to the corresponding delay metrics. Second, we?ll present how to build our open-source prototype Zeus both hardware and software design. Third, we?ll show the experiment results. Specifically, report the time consumption of the tasks across system components and discuss their effects on the start-up delay, event-to-eye delay, and frame rate. We also evaluate the time consumption of the tasks under varying impact factors to expose potential mitigation of long delay that affects user experience. Finally, we show that our results are representative by comparing with a commercial live 360° video streaming system.

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    • Published in

      cover image ACM Conferences
      MM '20: Proceedings of the 28th ACM International Conference on Multimedia
      October 2020
      4889 pages
      ISBN:9781450379885
      DOI:10.1145/3394171

      Copyright © 2020 ACM

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      Publication History

      • Published: 12 October 2020

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