Markov Based Rate Adaption Approach for Live Streaming over HTTP/2

doi:10.3969/j.issn.1673-5188.2018.02.007

ZTE Communications ›› 2018, Vol. 16 ›› Issue (2): 37-41.DOI: 10.3969/j.issn.1673-5188.2018.02.007

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Markov Based Rate Adaption Approach for Live Streaming over HTTP/2

XIE Lan¹, ZHANG Xinggong¹, HUANG Cheng², DONG Zhenjiang²

^1. Institute of Computer Science and Technology, Peking University, Beijing 100080, China
^2. ZTE Corporation, Nanjing 210012, China

Received:2017-01-01 Online:2018-06-25 Published:2019-12-12
About author:XIE Lan (xielan@pku.edu.cn) received the B.S. degree from Beijing University of Technology, China in 2015. She is currently a master degree student at the Institute of Computer Science and Technology, Peking University. Her research interests include dynamic HTTP streaming and VR video streaming. She received Beijing Outstanding Graduate Award in 2015.|ZHANG Xinggong (zhangxg@pku.edu.cn) received the Ph.D. degree from Peking University, China in 2011. He is currently a professor at the Institute of Computer Science and Technology, Peking University. His research interests include video conferencing, dynamic HTTP streaming, information-centric networking and VR video streaming. He received the First Prize of the Ministry of Education Science and Technology Progress Award in 2006 and the Second Prize of the National Science and Technology Award in 2007.|HUANG Cheng (huang.cheng5@zte.com.cn) received the M.S. degree from Southeast University, China in 2006. He is currently a senior system engineer and multimedia standard manager at ZTE Corporation. His research interest include video coding, storage, transport, and multimedia systems.|DONG Zhenjiang (dong.zhenjiang@zte.com.cn) received his M.S. degree in telecommunication from Harbin Institute of Technology, China in 1996. He is the deputy head of the Service Institute of ZTE Corporation and standing director of Chinese Association for Artificial Intelligence. His research interests include cloud computing, mobile internet, natural language processing, and multimedia analysis.
Supported by:
This work was supported in part by China “973” Program under Grant No. 2014CB340303” and ZTE Industry-Academia-Research Cooperation Funds.

Abstract

Abstract:

Dynamic adaptive streaming over HTTP (DASH) has been widely deployed. However, large latency in HTTP/1.1 cannot meet the requirements of live streaming. Data-pushing in HTTP/2 is emerging as a promising technology. For video live over HTTP/2, new challenges arise due to both low-delay and small buffer constraints. In this paper, we study the rate adaption problem over HTTP/2 with the aim to improve the quality of experience (QoE) of live streaming. To track the dynamic characteristics of the streaming system, a Markov-theoretical approach is employed. System variables are taken into account to describe the system state, by which the system transition probability is derived. Moreover, we design a dynamic reward function considering both the quality of user experience and dynamic system variables. Therefore, the rate adaption problem is formulated into a Markov decision based optimization problem and the best streaming policy is obtained. At last, the effectiveness of our proposed rate adaption scheme is demonstrated by numerous experiment results.

Key words: DASH, live, rate adaption, Markov decision

XIE Lan, ZHANG Xinggong, HUANG Cheng, DONG Zhenjiang. Markov Based Rate Adaption Approach for Live Streaming over HTTP/2[J]. ZTE Communications, 2018, 16(2): 37-41.

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References 13

[1]	S. Akhshabi, A. C. Begen, C. Dovrolis , “An experimental evaluation of rate-adaptation algorithms in adaptive streaming over http,” in Proc. 2nd Annual ACM Conference on Multimedia Systems, San Jose, USA, 2011, pp. 157-168. doi: 10.1145/1943552.1943574.
[2]	T. Stockhammer , “Dynamic adaptive streaming over http-: standards and design principles,” in Proc. 2nd Annual ACM Conference on Multimedia Systems, San Jose, USA, 2011, pp. 133-144. doi: 10.1145/1943552.1943572.
[3]	C. Zhou, X. Zhang, L. Huo, Z. Guo , “A control-theoretic approach to rate adaptation for dynamic http streaming,” in 2012 IEEE Visual Communications and Image Processing, San Diego, USA, 2012, pp. 1-6. doi: 10.1109/VCIP.2012. 6410740.
[4]	C. Zhou, C.-W. Lin, X. Zhang, and Z. Guo , “A control-theoretic approach to rate adaption for dash over multiple content distribution servers,” IEEE Transactions on Circuts and Systems for Video Technology, vol. 24, no. 4, pp. 681-694, Apr. 2014. doi: 10.1109/TCSVT.2013.2290580.
[5]	A. Zambelli , “IIS smooth streaming technical overview,” Microsoft Corporation, USA, vol. 3, 2009.
[6]	S. Garcia, J. Cabrera, N. Garcia , “Quality-control algorithm for adaptive streaming services over wireless channels,” IEEE Journal of Selected Topics in Signal Processing, vol. 9, no. 1, pp. 50-59, Feb. 2015. doi: 10.1109/JSTSP.2014.2331912. DOI URL
[7]	M. Xing, S. Xiang, L. Cai , “A real-time adaptive algorithm for video streaming over multiple wireless access networks,” IEEE Journal on Selected Areas in Communications, vol. 32, no. 4, pp. 795-805, Apr. 2014. doi: 10.1109/JSAC.2014.140411. DOI URL
[8]	T. Andelin, V, Chetty, D. Harbaugh, S. Warnick, and D. Zappala , “Quality selection for dynamic adaptive streaming over http with scalable video coding,” in Proc. 3rd Multimedia Systems Conference, Chapel Hill, USA, 2012, pp. 149-154. doi: 10.1145/2155555.2155580.
[9]	S. Xiang, L. Cai, J. Pan , “Adaptive scalable video streaming in wireless networks,” in Proc. 3rd Multimedia Systems Conference, Chapel Hill, USA, 2012, pp. 167-172. doi: 10.1145/2155555.2155583.
[10]	M. Xing, S. Xiang, L. Cai , “Rate adaptation strategy for video streaming over multiple wireless access networks,” in Proc. IEEE Global Communications Conference, Atlanta, USA, 2013, pp. 5745-5750.
[11]	C. Mueller, S. Lederer, C. Timmerer, H. Hellwagner , “Dynamic adaptive streaming over http/2.0,” in IEEE international Conference on Multimedia and Expo (ICME), San Jose, USA, 2013, pp. 1-6. doi: 10.1109/ICME.2013.6607498.
[12]	T. C. Thang, H. T. Le, A. T. Pham, Y. M. Ro , “An evaluation of bitrate adaptation methods for http live streaming,” IEEE Journal on Selected Areas in Communications, vol. 32, no. 4, pp. 693-705, Apr. 2014. doi: 10.1109/JSAC.2014.140403. DOI URL
[13]	S. Wei and V. Swaminathan , “Low latency live streaming over http2.0,” in Proc. Network and Operating System Support on Digital Audio and Video Workshop, Singapore, Singapore, 2014, pp. 37-37.

Markov Based Rate Adaption Approach for Live Streaming over HTTP/2

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