Mariem Ben Yahia
Gwendal Simon
Xavier Corbillon
Skip Abstract Section
Abstract
In this article, we propose video delivery schemes insuring around 1s delivery latency with Dynamic Adaptive Streaming over HTTP (DASH), which is a standard version of HTTP Live Streaming (HLS), so as to benefit from the video representation switching between successive video segments. We also propose HTTP/2-based algorithms to apply video frame discarding policies inside a video segment when a selected DASH representation does not match with the available network resources. The current solutions with small buffer suffer from rebuffering events. Rebuffering not only impacts the Quality of Experience (QoE) but also increases the delivery delay between the displayed and the original video streams. In this work, we completely eliminate rebuffering events by developing optimal and practical video frame discarding algorithms to meet the 1s latency constraint. In all our algorithms, we request the video frames individually through HTTP/2 multiple streams, and we selectively drop the least meaningful video frames thanks to HTTP/2 stream resetting feature. Our simulations show that the proposed algorithms eliminate rebuffering while insuring an acceptable video quality with at least a Peak Signal to Noise Ratio (PSNR) of 35dB compared to 25dB of the basic First In First Out (FIFO) algorithm. We also quantify and qualify the resulting temporal distortion of the video segments per algorithm. An important number of missing video frames results in a temporal fluidity break known as video jitter. The displayed video looks like a series of snapshots. We show that both the optimal Integer Linear Program (ILP) and practical algorithms decrease the frequency and duration of the jitters. For example, practical algorithms reduce the number of crashed displayed videos (presenting one jitter longer than 1,350ms) with 22% compared to the basic FIFO algorithm. We also show that requesting video frames separately with HTTP/2 slightly increases the overhead from 4.34% to 5.76%.
- Mike Belshe, Roberto Peon, and Martin Thomson. 2015. Hypertext Transfer Protocol Version 2 (HTTP/2) Standard. RFC 7540. IETF.Google Scholar
- Mariem Ben-Yahia, Yannick Le Louédec, Loutfi Nuaymi, and Gwendal Simon. 2017. When HTTP/2 rescues DASH: Video frame multiplexing. In Proceedings of the IEEE Conference on Computer Communications Workshops Workshops (INFOCOM’17). 677--682.Google ScholarCross Ref
- Nassima Bouzakaria, Cyril Concolato, and Jean Le Feuvre. 2014. Overhead and performance of low latency live streaming using MPEG-DASH. In Proceedings of the International Conference on Information, Intelligence, Systems and Applications (IISA’14). 92--97.Google ScholarCross Ref
- Nassima Bouzakaria, Cyril Concolato, and Jean Le Feuvre. 2015. Fast DASH bootstrap. In Proceedings of the IEEE International Workshop on Multimedia Signal Processing (MMSP’15).Google ScholarCross Ref
- Pete Campbell. 2016. Why Every Brand Needs to Migrate to HTTP/2 and How To Do It. Technical Report. State of Digital.Google Scholar
- Jacob Chakareski, John G. Apostolopoulos, Wai-tian Tan, Susie Wee, and Bernd Girod. 2004. Distortion chains for predicting the video distortion for general packet loss patterns. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’04). 1001--1004.Google ScholarCross Ref
- Yueh-Lun Chang, Ting-Lan Lin, and Pamela C. Cosman. 2012. Network-based H.264/AVC whole-frame loss visibility model and frame dropping methods. IEEE Trans. Image Process. 21, 8 (2012), 3353--3363. Google ScholarDigital Library
- Wael Chérif, Youenn Fablet, Eric Nassor, Jonathan Taquet, and Yuki Fujimori. 2015. DASH fast start using HTTP/2. In Proceedings of the ACM Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV’15). 25--30. Google ScholarDigital Library
- Cisco. 2017. Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2016--2021 White Paper.Google Scholar
- Conv. 2015. Viewer Experience Report 2015. Conviva Annual Report.Google Scholar
- Xavier Corbillon, Ramon Aparicio-Pardo, Nicolas Kuhn, Géraldine Texier, and Gwendal Simon. 2016a. Cross-layer scheduler for video streaming over MPTCP. In Proceedings of the International Conference on Multimedia Systems (MMSys’16). 7:1--7:12. Google ScholarDigital Library
- Xavier Corbillon, Florian Boyrivent, Gregoire Asselin De Williencourt, Gwendal Simon, Géraldine Texier, and Jacob Chakareski. 2016b. Efficient lightweight video packet filtering for large-scale video data delivery. In Proceedings of the IEEE International Conference on Multimedia 8 Expo Workshops (ICME’16). 1--6.Google ScholarCross Ref
- Khalid A. Darabkh, Abeer M. Awad, and Ala F. Khalifeh. 2014. Efficient PFD-based networking and buffering models for improving video quality over congested links. Wireless Pers. Commun. 79, 1 (2014), 293--320. Google ScholarDigital Library
- Khalid A. Darabkh, Abeer M. Awad, and Ala F. Khalifeh. 2015. New video discarding policies for improving UDP performance over wired/wireless networks. Int. J. Netw. Manage. 25, 3 (2015), 181--202. Google ScholarDigital Library
- Florin Dobrian, Asad Awan, Dilip Antony Joseph, Aditya Ganjam, Jibin Zhan, Vyas Sekar, Ion Stoica, and Hui Zhang. 2013. Understanding the impact of video quality on user engagement. Commun. ACM 56, 3 (2013), 91--99. Google ScholarDigital Library
- Zhengfang Duanmu, Kai Zeng, Kede Ma, Abdul Rehman, and Zhou Wang. 2017. A quality-of-experience index for streaming video. J. Sel. Top. Sign. Process. 11, 1 (2017), 154--166.Google ScholarCross Ref
- Jean Le Feuvre, Cyril Concolato, Nassima Bouzakaria, and Viet-Thanh-Trung Nguyen. 2015. MPEG-DASH for low latency and hybrid streaming services. In Proceedings of the Annual ACM Conference on Multimedia Conference (MM’15). 751--752. Google ScholarDigital Library
- Deepak Gangadharan, Linh T. X. Phan, Samarjit Chakraborty, Roger Zimmermann, and Insup Lee. 2011. Video quality driven buffer sizing via frame drops. In Proceedings of the IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA’11), Volume 1. 319--328. Google ScholarDigital Library
- Patrice Houze, Emmanuel Mory, Géraldine Texier, and Gwendal Simon. 2016. Applicative-layer multipath for low-latency adaptive live streaming. In Proceedings of the IEEE International Conference on Communications (ICC’16). 1--7.Google ScholarCross Ref
- Quan Huynh-thu and Mohammed Ghanbari. 2006. Impact of jitter and jerkiness on perceived video quality. In Proceedings of the Second International Workshop on Video Processing and Quality Metrics for Consumer Electronics, (VPQM’06).Google Scholar
- Rafael Huysegems, Tom Bostoen, Patrice Rondao-Alface, Jeroen van der Hooft, Stefano Petrangeli, Tim Wauters, and Filip De Turck. 2015. HTTP/2-based methods to improve the live experience of adaptive streaming. In Proceedings of the Annual ACM Conference on Multimedia Conference (MM’15). Google ScholarDigital Library
- ISO. 2012a. Coding of Audio-visual Objects—Part 10: Advanced Video Coding. Technical Report 14496-10. ISO/IEC.Google Scholar
- ISO. 2012b. Dynamic Adaptive Streaming Over HTTP (DASH). Technical Report 23009. ISO/IEC.Google Scholar
- ISO. 2015. Information Technology--High Efficiency Coding and Media Delivery in Heterogeneous Environments--Part 2: High Efficiency Video Coding. Technical Report 23008-2. ISO/IEC.Google Scholar
- Athina Kalampogia and Polychronis Koutsakis. 2018. H.264 and H.265 video bandwidth prediction. IEEE Trans. Multimedia 20, 1 (2018), 171--182. Google ScholarDigital Library
- Theodoros Karagkioules, Cyril Concolato, Dimitrios Tsilimantos, and Stefan Valentin. 2017. A comparative case study of HTTP adaptive streaming algorithms in mobile networks. In Proceedings of the Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV’17). 1--6. Google ScholarDigital Library
- S. Shunmuga Krishnan and Ramesh K. Sitaraman. 2013. Video stream quality impacts viewer behavior: Inferring causality using quasi-experimental designs. IEEE/ACM Trans. Netw. 21, 6 (2013), 2001--2014. Google ScholarDigital Library
- Jonathan Kua, Grenville Armitage, and Philip Branch. 2017. A survey of rate adaptation techniques for dynamic adaptive streaming over HTTP. IEEE Commun. Surv. Tutor. 19, 3 (2017), 1842--1866.Google ScholarDigital Library
- Ke Liu and Jack Y. B. Lee. 2015. Achieving high throughput and low delay in mobile data networks by accurately predicting queue lengths. In Proceedings of the ACM International Conference on Computing Frontiers (CF’15). 20:1--20:8. Google ScholarDigital Library
- Linh Van Ma, Jaehyung Park, Jiseung Nam, HoYong Ryu, and Jinsul Kim. 2017. A fuzzy-based adaptive streaming algorithm for reducing entropy rate of DASH bitrate fluctuation to improve mobile quality of service. Entropy 19, 9 (2017), 477.Google ScholarCross Ref
- Saied Mehdian and Ben Liang. 2014. Jointly optimal selection and scheduling for lossy transmission of dependent frames with delay constraint. In Proceedings of the IEEE International Symposium of Quality of Service (IWQoS’14). 168--177.Google ScholarCross Ref
- Ricky K. P. Mok, Xiapu Luo, Edmond W. W. Chan, and Rocky K. C. Chang. 2012. QDASH: A QoE-aware DASH system. In Proceedings of the Annual ACM SIGMM Conference on Multimedia Systems (MMSys’12). 11--22. Google ScholarDigital Library
- Christopher Müller, Stefan Lederer, Christian Timmerer, and Hermann Hellwagner. 2013. Dynamic adaptive streaming over HTTP/2.0. In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME’13). 1--6.Google ScholarCross Ref
- Ricardo Pastrana-Vidal and Jean-Charles Gicquel. 2006. Automatic quality assessment of video fluidity impairment using a no-reference metric. In Proceedings of Workshop Video Process. Quality Metrics for Consumer Electron (VPQM’06).Google Scholar
- Alassane Samba, Yann Busnel, Alberto Blanc, Philippe Dooze, and Gwendal Simon. 2017. Instantaneous throughput prediction in cellular networks: Which information is needed? In Proceedings of the IFIP/IEEE Symposium on Integrated Network and Service Management (IM’17). 624--627.Google ScholarCross Ref
- Michael Seufert, Sebastian Egger, Martin Slanina, Thomas Zinner, Tobias Hoßfeld, and Phuoc Tran-Gia. 2015. A survey on quality of experience of HTTP adaptive streaming. IEEE Commun. Surv. Tutor. 17, 1 (2015), 469--492.Google ScholarDigital Library
- Kevin Spiteri, Ramesh Sitaraman, and Daniel Sparacio. 2018. From theory to practice: Improving bitrate adaptation in the DASH reference player. In Proceedings of the ACM Multimedia Systems Conference (MMSys’18). Google ScholarDigital Library
- Viswanathan Swaminathan and Sheng Wei. 2011. Low latency live video streaming using HTTP chunked encoding. In Proceedings of the IEEE International Workshop on Multimedia Signal Processing (MMSP’11). 1--6.Google ScholarCross Ref
- Truong Cong Thang, Quang-Dung Ho, Jung Won Kang, and Anh T. Pham. 2012. Adaptive streaming of audiovisual content using MPEG DASH. IEEE Trans. Consum. Electron. 58, 1 (2012), 78--85.Google ScholarCross Ref
- Christian Timmerer and Alan Bertoni. 2016. Advanced transport options for the dynamic adaptive streaming over HTTP. CoRR abs/1606.00264 (2016).Google Scholar
- S. van Kester, T. Xiao, Robert E. Kooij, Kjell Brunnström, and O. K. Ahmed. 2011. Estimating the impact of single and multiple freezes on video quality. In Proceedings of the Human Vision and Electronic Imaging XVI, part of the IS&T-SPIE Electronic Imaging Symposium. 78650O.Google Scholar
- Sheng Wei, Viswanathan Swaminathan, and Mengbai Xiao. 2015a. Power efficient mobile video streaming using HTTP/2 server push. In Proceedings of the IEEE International Workshop on Multimedia Signal Processing (MMSP’15). 1--6.Google ScholarCross Ref
- Sheng Wei, Viswanathan Swaminathan, and Mengbai Xiao. 2015b. Power efficient mobile video streaming using HTTP/2 server push. In Proceedings of the ACM International Workshop on Multimedia Signal Processing (MMSP’15).Google ScholarCross Ref
- Nicolas Weil. 2016. The State of MPEG-DASH 2016. Technical Report 23009. Streaming Media.Google Scholar
- Thomas Wiegand, Gary J. Sullivan, Gisle Bjøntegaard, and Ajay Luthra. 2003. Overview of the H.264/AVC video coding standard. IEEE Trans. Circuits Syst. Video Technol. 13, 7 (2003), 560--576. Google ScholarDigital Library
- Mengbai Xiao, Viswanathan Swaminathan, Sheng Wei, and Songqing Chen. 2016. Evaluating and improving push based video streaming with HTTP/2. In Proceedings of the International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV’16). 3:1--3:6. Google ScholarDigital Library
- Xiph.org. 1994-2016. Xiph.org Test Media. Retrieved from https://media.xiph.org/video/derf/.Google Scholar
Index Terms
- HTTP/2-based Frame Discarding for Low-Latency Adaptive Video Streaming
Recommendations
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 ...
Performance of Low-Latency HTTP-based Streaming Players
MHV '23: Proceedings of the 2nd Mile-High Video ConferenceReducing end-to-end streaming latency is critical to HTTP-based live video streaming. There are currently two main technologies in this domain: Low-Latency HTTP Live Streaming (LL-HLS) and Low-Latency Dynamic Adaptive Streaming over HTTP (LL-DASH). ...
An SDN-aided low-latency live video streaming over HTTP
AbstractDynamic adaptive streaming over HTTP (DASH) is the crucial factor in the rapid penetration of over-the-top (OTT) service providers for on-demand video streaming. It can also be used for live video streaming by the OTT providers. The recent ...
Comments