Yu Wang
ABSTRACT
Adaptive streaming over HTTP/2 has recently caught attention in the development of multimedia delivery. The server push feature of HTTP/2 enables the streaming server to send multiple video segments to the clients within a single request, therefore reducing unnecessary overheads, RTTs and energy consumption on portable devices, also empowering the use of short segment duration to improve network adaptability. However, recent researches only investigate the performance of the HTTP/2 server push under a single-client scenario. In fact, when multiple clients share a limited bottleneck bandwidth, it is highly possible that the unfairness in bitrate selection will happen due to the mismatch of the segment download state among the clients. In this paper, we hypothetically discuss various cases that a client decides its bitrate higher or lower than one another. Then, an experiment with the DASH.js player under several scenarios is provided to confirm the reliability of our hypothesis.
- Sheng Wei and Viswanathan Swaminathan. 2014. Low Latency Live Video Streaming over HTTP 2.0. In Proceedings of Network and Operating System Support on Digital Audio and Video Workshop (NOSSDAV '14). ACM, New York, NY, USA, Article 37, 6 pages. https://doi.org/10.1145/2597176.2578277Google Scholar
Digital Library
- S. Wei and V. Swaminathan. 2014. Cost effective video streaming using server push over HTTP 2.0. In 2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP). 1--5. https://doi.org/10.1109/MMSP.2014.6958796Google ScholarCross Ref
- S. Wei, V. Swaminathan, and Mengbai Xiao. 2015. Power efficient mobile video streaming using HTTP/2 server push. In 2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP). 1--6. https://doi.org/10.1109/MMSP.2015.7340877Google ScholarCross Ref
- Jeroen van der Hooft, Stefano Petrangeli, Tim Wauters, Rafael Huysegems, Tom Bostoen, and Filip De Turck. 2018. An HTTP/2 Push-Based Approach for Low-Latency Live Streaming with Super-Short Segments. Journal of Network and Systems Management 26, 1 (01 Jan 2018), 51--78. https://doi.org/10.1007/s10922--017-9407--2Google ScholarCross Ref
- RFC: 7540 Hypertext Transfer Protocol Version 2 (HTTP/2). 2015. https://tools.ietf.org/html/rfc7540Google Scholar
- Saamer Akhshabi, Lakshmi Anantakrishnan, Ali C. Begen, and Constantine Dovrolis. 2012. What happens when HTTP adaptive streaming players compete for bandwidth?. In Proceedings of the 22nd international workshop on Network and Operating System Support for Digital Audio and Video (NOSSDAV '12). ACM, New York, NY, USA, 9--14. http://dx.doi.org/10.1145/2229087.2229092Google ScholarDigital Library
- Z. Li, X. Zhu, J. Gahm, R. Pan, H. Hu, A. C. Begen, and D. Oran. 2014. Probe and Adapt: Rate Adaptation for HTTP Video Streaming At Scale. IEEE Journal onSelected Areas in Communications 32, 4 (April 2014), 719--733. https://doi.org/10.1109/JSAC.2014.140405Google ScholarCross Ref
- Saamer Akhshabi, Ali C. Begen, and Constantine Dovrolis. 2011. An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP. In Proceedings of the second annual ACM conference on Multimedia systems (MMSys '11). ACM, New York, NY, USA, 157--168. https://doi.org/10.1145/1943552.1943574Google ScholarDigital Library
- J. Jiang, V. Sekar, and H. Zhang. 2014. Improving Fairness, Efficiency, and Stability in HTTP-Based Adaptive Video Streaming With Festive. IEEE/ACM Transactions on Networking 22, 1 (Feb 2014), 326--340. https://doi.org/ 10.1109/TNET.2013.2291681Google ScholarCross Ref
- Te-Yuan Huang, Ramesh Johari, Nick McKeown, Matthew Trunnell, and Mark Watson. 2014. A Buffer-based Approach to Rate Adaptation: Evidence from a Large Video Streaming Service. SIGCOMM Comput. Commun. Rev. 44, 4 (Aug. 2014), 187--198. https://doi.org/10.1145/2740070.2626296Google ScholarDigital Library
- K. Spiteri, R. Urgaonkar, and R. K. Sitaraman. 2016. BOLA: Near-optimal bitrate adaptation for online videos. In IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications. 1--9. https://doi.org/ 10.1109/INFOCOM.2016.7524428Google ScholarDigital Library
- R. Jain, D. Chiu and W. Hawe. 1984. A quantitative measure of fairness and discrimination for resource allocation in shared computer system.Google Scholar
Index Terms
- An Experimental Study on The Unfairness in Adaptive Streaming with HTTP/2 Server Push
Recommendations
An HTTP/2-Based Adaptive Streaming Framework for 360° Virtual Reality Videos
MM '17: Proceedings of the 25th ACM international conference on MultimediaVirtual Reality (VR) devices are becoming accessible to a large public, which is going to increase the demand for 360° VR videos. VR videos are often characterized by a poor quality of experience, due to the high bandwidth required to stream the 360° ...
HTTP/2-Based Methods to Improve the Live Experience of Adaptive Streaming
MM '15: Proceedings of the 23rd ACM international conference on MultimediaHTTP Adaptive Streaming (HAS) is today the number one video technology for over-the-top video distribution. In HAS, video content is temporally divided into multiple segments and encoded at different quality levels. A client selects and retrieves per ...
An HTTP/2 Push-Based Approach for Low-Latency Live Streaming with Super-Short Segments
Over the last years, streaming of multimedia content has become more prominent than ever. To meet increasing user requirements, the concept of HTTP Adaptive Streaming (HAS) has recently been introduced. In HAS, video content is temporally divided into ...
Comments