Tightrope walking in low-latency live streaming: optimal joint adaptation of video rate and playback speed

ABSTRACT

It is highly challenging to simultaneously achieve high-rate and low-latency in live video streaming. Chunk-based streaming and playback speed adaptation are two promising new trends to achieve high user Quality-of-Experience (QoE). To thoroughly understand their potentials, we develop a detailed chunk-level dynamic model that characterizes how video rate and playback speed jointly control the evolution of a live streaming session. Leveraging on the model, we first study the optimal joint video rate-playback speed adaptation as a non-linear optimal control problem. We further develop model-free joint adaptation strategies using deep reinforcement learning. Through extensive experiments, we demonstrate that our proposed joint adaptation algorithms significantly outperform rate-only adaptation algorithms and the recently proposed low-latency video streaming algorithms that separately adapt video rate and playback speed without joint optimization. In a wide-range of network conditions, the model-based and model-free algorithms can achieve close-to-optimal trade-offs tailored for users with different QoE preferences.

References

1. [n.d.]. ACM MMSys 2020 grand challenge. https://github.com/twitchtv/acm-mmsys-2020-grand-challenge
2. [n.d.]. Live Streaming vs. Traditional Live Broadcasting: What's the Difference. https://www.wowza.com/blog/streaming-vs-cable-satellite-broadcasting
3. [n.d.]. Video Streaming Latency Report. https://www.wowza.com/wp-content/uploads/Streaming-Video-Latency-Report-Interactive-2020.pdf
4. Zahaib Akhtar, Yun Seong Nam, Ramesh Govindan, Sanjay Rao, Jessica Chen, Ethan Katz-Bassett, Bruno Ribeiro, Jibin Zhan, and Hui Zhang. 2018. Oboe: auto-tuning video ABR algorithms to network conditions. In Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication. 44--58.
5. Alberto Bemporad, Manfred Morari, Vivek Dua, and Efstratios N Pistikopoulos. 2002. The explicit linear quadratic regulator for constrained systems. Automatica 38, 1 (2002), 3--20.
6. Abdelhak Bentaleb, Praveen Kumar Yadav, Wei Tsang Ooi, and Roger Zimmermann. 2020. DQ-DASH: A Queuing Theory Approach to Distributed Adaptive Video Streaming. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) 16, 1 (2020), 1--24.
7. Nassima Bouzakaria, Cyril Concolato, and Jean Le Feuvre. 2014. Overhead and performance of low latency live streaming using MPEG-DASH. In IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications. IEEE, 92--97.
8. Wael Cherif, Youenn Fablet, Eric Nassor, Jonathan Taquet, and Yuki Fujimori. 2015. DASH fast start using HTTP/2. In Proceedings of the 25th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video. 25--30.
9. Leana Golubchik, John CS Lui, and Richard Muntz. 1995. Reducing I/O demand in video-on-demand storage servers. In Proceedings of the 1995 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems. 25--36.
10. Craig Gutterman, Brayn Fridman, Trey Gilliland, Yusheng Hu, and Gil Zussman. 2020. Stallion: video adaptation algorithm for low-latency video streaming. In Proceedings of the 11th ACM Multimedia Systems Conference. 327--332.
11. Te-Yuan Huang, Ramesh Johari, Nick McKeown, Matthew Trunnell, and Mark Watson. 2015. A buffer-based approach to rate adaptation: Evidence from a large video streaming service. ACM SIGCOMM Computer Communication Review 44, 4 (2015), 187--198.
12. ISO. 2013. Common media application format (CMAF) for segmented media. https://www.iso.org/standard/71975.html
13. Junchen Jiang, Vyas Sekar, and Hui Zhang. 2012. Improving fairness, efficiency, and stability in http-based adaptive video streaming with festive. In Proceedings of the 8th international conference on Emerging networking experiments and technologies. 97--108.
14. Xiaolan Jiang and Yusheng Ji. 2019. HD3: Distributed Dueling DQN with Discrete-Continuous Hybrid Action Spaces for Live Video Streaming. In Proceedings of the 27th ACM International Conference on Multimedia. 2632--2636.
15. Mark Kalman, Eckehard Steinbach, and Bernd Girod. 2004. Adaptive media play-out for low-delay video streaming over error-prone channels. IEEE Transactions on Circuits and Systems for Video Technology 14, 6 (2004), 841--851.
16. Theo Karagkioules, Rufael Mekuria, Dirk Griffioen, and Arjen Wagenaar. 2020. Online learning for low-latency adaptive streaming. In Proceedings of the 11th ACM Multimedia Systems Conference. 315--320.
17. Zhi Li, Xiaoqing Zhu, Joshua Gahm, Rong Pan, Hao Hu, Ali C Begen, and David Oran. 2014. Probe and adapt: Rate adaptation for HTTP video streaming at scale. IEEE Journal on Selected Areas in Communications 32, 4 (2014), 719--733.
18. May Lim, Mehmet N Akcay, Abdelhak Bentaleb, Ali C Begen, and Roger Zimmermann. 2020. When they go high, we go low: low-latency live streaming in dash. js with LoL. In Proceedings of the 11th ACM Multimedia Systems Conference. 321--326.
19. Chenghao Liu, Imed Bouazizi, and Moncef Gabbouj. 2011. Rate adaptation for adaptive HTTP streaming. In Proceedings of the second annual ACM conference on Multimedia systems. 169--174.
20. Chenghao Liu, Imed Bouazizi, Miska M Hannuksela, and Moncef Gabbouj. 2012. Rate adaptation for dynamic adaptive streaming over HTTP in content distribution network. Signal Processing: Image Communication 27, 4 (2012), 288--311.
21. Hongzi Mao, Ravi Netravali, and Mohammad Alizadeh. 2017. Neural adaptive video streaming with pensieve. In Proceedings of the Conference of the ACM Special Interest Group on Data Communication. ACM, 197--210.
22. Lifan Mei, Runchen Hu, Houwei Cao, Yong Liu, Zifa Han, Feng Li, and Jin Li. 2019. Realtime Mobile Bandwidth Prediction Using LSTM Neural Network. In International Conference on Passive and Active Network Measurement. Springer, 34--47.
23. Konstantin Miller, Emanuele Quacchio, Gianluca Gennari, and Adam Wolisz. 2012. Adaptation algorithm for adaptive streaming over HTTP. In 2012 19th international packet video workshop (PV). IEEE, 173--178.
24. Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller. 2013. Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602 (2013).
25. Haitian Pang, Zhi Wang, Chen Yan, Qinghua Ding, Kun Yi, Jiangchuan Liu, and Lifeng Sun. 2018. Content Harvest Network: Optimizing First Mile for Crowdsourced Live Streaming. IEEE Transactions on Circuits and Systems for Video Technology 29, 7 (2018), 2112--2125.
26. Roger Pantos and William May. 2017. HTTP live streaming. Technical Report.
27. Huan Peng, Yuan Zhang, Yongbei Yang, and Jinyao Yan. 2019. A Hybrid Control Scheme for Adaptive Live Streaming. In Proceedings of the 27th ACM International Conference on Multimedia. 2627--2631.
28. Satadal Sengupta, Niloy Ganguly, Sandip Chakraborty, and Pradipta De. 2018. HotDASH: Hotspot Aware Adaptive Video Streaming Using Deep Reinforcement Learning. In 2018 IEEE 26th International Conference on Network Protocols (ICNP). IEEE, 165--175.
29. Iraj Sodagar. 2011. The mpeg-dash standard for multimedia streaming over the internet. IEEE MultiMedia 18, 4 (2011), 62--67.
30. Kevin Spiteri, Rahul Urgaonkar, and Ramesh K Sitaraman. 2016. BOLA: Near-optimal bitrate adaptation for online videos. In IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on Computer Communications. IEEE, 1--9.
31. Eckehard Steinbach, Niko Farber, and Bernd Girod. 2001. Adaptive playout for low latency video streaming. In Proceedings 2001 International Conference on Image Processing (Cat. No. 01CH37205), Vol. 1. IEEE, 962--965.
32. Kairan Sun and Dapeng Wu. 2016. MPC-based delay-aware fountain codes for live video streaming. In 2016 IEEE international conference on communications (ICC). IEEE, 1--6.
33. Liyang Sun, Yixiang Mao, Tongyu Zong, Yong Liu, and Yao Wang. 2020. Flocking-based live streaming of 360-degree video. In Proceedings of the 11th ACM Multi-media Systems Conference. 26--37.
34. Liyang Sun, Tongyu Zong, Yong Liu, Yao Wang, and Haihong Zhu. 2019. Optimal Strategies for Live Video Streaming in the Low-latency Regime. In 2019 IEEE 27th International Conference on Network Protocols (ICNP). IEEE, 1--4.
35. Viswanathan Swaminathan and Sheng Wei. 2011. Low latency live video streaming using HTTP chunked encoding. In 2011 IEEE 13th International Workshop on Multimedia Signal Processing. IEEE, 1--6.
36. Arash Tavakoli, Fabio Pardo, and Petar Kormushev. 2018. Action branching architectures for deep reinforcement learning. In Thirty-Second AAAI Conference on Artificial Intelligence.
37. Guibin Tian and Yong Liu. 2012. Towards agile and smooth video adaptation in dynamic HTTP streaming. In Proceedings of the 8th international conference on Emerging networking experiments and technologies. 109--120.
38. Emanuel Todorov and Weiwei Li. 2005. A generalized iterative LQG method for locally-optimal feedback control of constrained nonlinear stochastic systems. In Proceedings of the 2005, American Control Conference, 2005. IEEE, 300--306.
39. 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 (2018), 51--78.
40. Chen Wang, Jianfeng Guan, Tongtong Feng, Neng Zhang, and Tengfei Cao. 2019. BitLat: Bitrate-adaptivity and Latency-awareness Algorithm for Live Video Streaming. In Proceedings of the 27th ACM International Conference on Multimedia. 2642--2646.
41. Ziyu Wang, Tom Schaul, Matteo Hessel, Hado Hasselt, Marc Lanctot, and Nando Freitas. 2016. Dueling network architectures for deep reinforcement learning. In International conference on machine learning. PMLR, 1995--2003.
42. Wikipedia contributors. 2021. Chunked transfer encoding --- Wikipedia, The Free Encyclopedia. https://en.wikipedia.org/w/index.php?title=Chunked_transfer_encoding&oldid=997959340 [Online; accessed 5-March-2021].
43. Lan Xie, Chao Zhou, Xinggong Zhang, and Zongming Guo. 2017. Dynamic threshold based rate adaptation for HTTP live streaming. In 2017 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 1--4.
44. Gang Yi, Dan Yang, Abdelhak Bentaleb, Weihua Li, Yi Li, Kai Zheng, Jiangchuan Liu, Wei Tsang Ooi, and Yong Cui. 2019. The ACM Multimedia 2019 Live Video Streaming Grand Challenge. In Proceedings of the 27th ACM International Conference on Multimedia. 2622--2626.
45. Xiaoqi Yin, Abhishek Jindal, Vyas Sekar, and Bruno Sinopoli. 2015. A control-theoretic approach for dynamic adaptive video streaming over HTTP. In ACM SIGCOMM Computer Communication Review, Vol. 45. ACM, 325--338.
46. Guanghui Zhang and Jack YB Lee. 2019. LAPAS: Latency-aware playback-adaptive streaming. In 2019 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 1--6.
47. Yin Zhao, Qi-Wei Shen, Wei Li, Tong Xu, Wei-Hua Niu, and Si-Ran Xu. 2019. Latency Aware Adaptive Video Streaming using Ensemble Deep Reinforcement Learning. In Proceedings of the 27th ACM International Conference on Multimedia. 2647--2651.
48. Chao Zhou, Xinggong Zhang, Longshe Huo, and Zongming Guo. 2012. A control-theoretic approach to rate adaptation for dynamic HTTP streaming. In 2012 Visual Communications and Image Processing. IEEE, 1--6.

Index Terms

• Computing methodologies

  • Machine learning

    • Learning paradigms

      • Reinforcement learning

• Information systems

  • Information systems applications

    • Multimedia information systems

      • Multimedia streaming