Personalized live video streaming is an increasingly popular technology that allows a broadcaster to share videos in real time with worldwide viewers. Compared to video-on-demand (VOD) streaming, experimenting with personalized live video streaming is harder due to its intrinsic live nature, the need for worldwide viewers, and a more complex data collection pipeline. In this paper, we make several contributions to both experimenting with and understanding today's commercial live video streaming services. First, we develop LIME (Live video MEasurement platform), a generic and holistic system allowing researchers to conduct crowd-sourced measurements on both commercial and experimental live streaming platforms. Second, we use LIME to perform, to the best of our knowledge, a first study of personalized 360°live video streaming on two commercial platforms, YouTube and Facebook. During a 7-day study, we have collected a dataset from 548 paid Amazon Mechanical Turk viewers from 35 countries who have watched more than 4,000 minutes of 360°live videos. Using this unique dataset, we characterize 360°live video streaming performance in the wild. Third, we conduct controlled experiments through LIME to shed light on how to make 360°live streaming (more) adaptive in the presence of challenging network conditions.
|Original language||English (US)|
|Title of host publication||Proceedings of the 10th ACM Multimedia Systems Conference, MMSys 2019|
|Publisher||Association for Computing Machinery, Inc|
|Number of pages||11|
|State||Published - Jun 18 2019|
|Event||10th ACM Multimedia Systems Conference, MMSys 2019 - Amherst, United States|
Duration: Jun 18 2019 → Jun 21 2019
|Name||Proceedings of the 10th ACM Multimedia Systems Conference, MMSys 2019|
|Conference||10th ACM Multimedia Systems Conference, MMSys 2019|
|Period||6/18/19 → 6/21/19|
Bibliographical noteFunding Information:
We thank the anonymous reviewers for their valuable comments. We also thank Prof. Kevin Almeroth for shepherding our paper. Feng Qian’s research was supported in part by NSF Award #1750890 and a Google Faculty Award.
© 2019 ACM.
- Crowd-sourced measurement
- Live video streaming