Adaptive Mobile Video Delivery Based on Fountain Codes and DASH: A Survey

doi:10.19729/j.cnki.1673-5188.2018.03.003

ZTE Communications ›› 2018, Vol. 16 ›› Issue (3): 9-14.DOI: 10.19729/j.cnki.1673-5188.2018.03.003

• Special Topic • Previous Articles Next Articles

Adaptive Mobile Video Delivery Based on Fountain Codes and DASH: A Survey

WU Kesong¹, CAO Xianbin¹, CHEN Zhifeng², WU Dapeng³

1.Beihang University, Beijing 100191, China
2.Fuzhou University, Fuzhou 350116, China
3.University of Florida, Gainesville 32611, USA

Online:2018-08-25 Published:2020-03-18
About author:WU Dapeng (dpwu@ufl.edu) is a professor at the Department of Electrical and Computer Engineering, University of Florida, USA. His research interests are in the areas of networking, communications, signal processing, computer vision, machine learning, smart grid, and information and network security. He serves as Editor in Chief and Associate Editor of multiple IEEE journals. He was the founding Editor-in-Chief of Journal of Advances in Multimedia. He has served as a member of executive committees and/or technical program committees of over 80 conferences. He is an IEEE Fellow.|CAO Xianbin (xbcao@buaa.edu.cn) is the Dean and a professor at the School of Electronic and Information Engineering, Beihang University, China. His current research interests include intelligent transportation systems, airspace transportation management, and intelligent computation. Currently, he serves as Associate Editor of IEEE Transactions on Network Science and Engineering, and Associate Editor of Neurocomputing.|CHEN Zhifeng (10799126@qq.com) received the Ph.D. degree in electrical and computer engineering from the University of Florida, USA in 2010. He is a professor with the College of Physics and Information Engineering, Fuzhou University, China. His research interests include video coding, video transmission, computer vision, machine learning, etc.

Abstract

Abstract:

Recent years have witnessed an explosive growth in mobile video-based services and efficient and reliable video delivery draws more and more attention. As a type of rateless codes, fountain codes can automatically adapt to wireless channel conditions without any knowledge of channels. This paper provides an overview of several typical Forward Error Correction (FEC) codes, such as Reed-Solomon (RS) code, Tornado code, Luby-Transform (LT) code, and Raptor code. We focus on a novel delay-aware fountain coding (DAF) technique that maximizes the code word length under the constraint of a given delay. Based on DAF, this paper also presents Unequal Error Protection DAF (UEP-DAF) which improves the Peak Signal to Noise Ratio (PSNR) without additional coordination between the encoder and the decoder, as well as Model Predictive Control DAF (MPC-DAF) which reduces the computational complexity to an affordable level for real-time video communications. Moreover, we review video streaming technologies, then introduce Dynamic Adaptive Streaming over HTTP (DASH) and DASH over Multiple Content Distribution Servers (MCDS-DASH) in detail. Based on MCDS-DASH that adapts video bitrate at the block level to alleviate video fluctuation, we propose a novel approach to integrating fountain codes with MCDS-DASH, which is capable of achieving unprecedented high throughput.

Key words: mobile video delivery, DAF, UEP, MPC, DASH

WU Kesong, CAO Xianbin, CHEN Zhifeng, WU Dapeng. Adaptive Mobile Video Delivery Based on Fountain Codes and DASH: A Survey[J]. ZTE Communications, 2018, 16(3): 9-14.

Figures/Tables 8

Figure 1. Development of typical erasure codes.

Figure 2. Block coding.

Figure 3. Sliding window coding.

Figure 4. Common intermediate format (CIF) sequence foreman.

Figure 5. IDR vs. the code rate of four window schemes.

Figure 6. Expanding window coding.

Figure 7. UEP by duplicating Mib packets.

Figure 8. ASP of three sampling schemes.

References 20

[1]	M. Luby , “LT codes,” in 43rd Annual IEEE Symposium on Foundations of Computer Science (FOCS), Vancouver, Canada, 2002, pp. 271-280.
[2]	A. Shokrollahi , “Raptor codes,” IEEE Transactions on Information Theory, vol. 52, no. 6, pp. 2551-2567, 2006. doi: 10.1109/TIT.2006.874390.
[3]	S. Ahmad, R. Hamzaoui, M.M Al-Akaidi . , “Unequal error protection using fountain codes with applications to video communication,” IEEE Transactions on Multimedia, vol. 13, no. 1, pp. 92-101, 2011. doi: 10.1109/TMM.2010.2093511.
[4]	M. C. Bogino, P. Cataldi, M. Grangetto, E. Magli, G. Olmo , “Sliding-window digital fountain codes for streaming of multimedia contents,” in IEEE International Symposium on Circuits and Systems, New Orleans, USA, May 2007, pp. 3467-3470. doi: 10.1109/ISCAS.2007.378373.
[5]	D. Sejdinovic, D. Vukobratovic, A. Doufexi, V. Senk, R. J. Piechocki , “Expanding window fountain codes for unequal error protection,” IEEE Transactions on Communications, vol. 57, no. 9, pp. 2510-2516, 2009. doi: 10.1109/TCOMM.2009.09.070616.
[6]	D. Vukobratovic, V. Stankovic, D. Sejdinovic, L. Stankovic, Z. Xiong , “Scalable video multicast using expanding window fountain codes,” IEEE Transactions on Multimedia, vol. 11, no. 6, pp. 1094-1104, 2009. doi: 10.1109/TMM.2009.2026087.
[7]	K. Sun, H. Zhang, D. Wu. (2016). Delay-aware fountain codes for video streaming with optimal sampling strategy [Online]. Available:
[8]	K. Sunand D. Wu, “Unequal error protection for video streaming using delay-aware fountain codes,” in IEEE ICC 2017 Communications Software, Services, and Multimedia Applications Symposium, Paris, France, May 2017. doi: 10.1109/ICC.2017.7996740.
[9]	N. Rahnavard and F. Fekri. “Finite-length unequal error protection rateless codes: design and analysis,” in Global Telecommunications Conference, St. Louis, USA, Dec. 2005. doi: 10.1109/GLOCOM.2005.1577872.
[10]	A. Talari and N. Rahnavard, “Distributed unequal error protection rateless codes over erasure channels: a two-source scenario,” IEEE Transactions on Communications, vol. 60, no. 8, pp. 2084-2090, 2012. doi: 10.1109/TCOMM.2012.051512.110109.
[11]	N. Rahnavard, B. N. Vellambi, F. Fekri , “Rateless codes with unequal error protection property,” IEEE Transactions on Information Theory, vol. 53, no. 4, pp. 1521-1532, 2007. doi: 10.1109/TIT.2007.892814.
[12]	K. Sun and D. Wu, “MPC-based delay-aware fountain codes for live video streaming,” in 2016 IEEE International Conference on Communications(ICC), Kuala Lumpur, Malaysia, May 2016, pp. 1-6. doi: 10.1109/ICC.2016.7510691.
[13]	C. Müller andC. Timmerer, “A test-bed for the dynamic adaptive streaming over HTTP featuring session mobility,” in Second Annual ACM Conference on Multimedia Systems, 2011, pp. 271-276. doi: 10.1145/1943552.1943588.
[14]	A. Begen, T. Akgul, M. Baugher , “Watching video over the web: part 1: streaming protocols,” IEEE Internet Computing, vol. 15, no.2, pp. 54-63, Mar. 2011. doi: 10.1109/MIC.2010.155.
[15]	R. Kuschnig, I. Kofler, H. Hellwagner , “Evaluation of HTTP-based request-response streams for Internet video streaming,” in Proc. ACM MMSys11, Feb.2011, pp. 245-256.
[16]	T. Ojanperä, H. Kokkoniemi-Tarkkanen , “Wireless bandwidth management for multiple video clients through network-assisted DASH,” in IEEE 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks, Coimbra, Portugal, Jun. 2016. doi: 10.1109/WoWMoM.2016.7523530.
[17]	C. Müller, D. Renzi, S. Lederer, S. Battista, C. Timmerer , “Using scalable video coding for dynamic adaptive streaming over HTTP in mobile environments,” in 20th European Signal Processing Conference (EUSIPCO 2012), Bucharest, Romania, Aug., 2012, pp. 2208-2212.
[18]	X. Yin, A. Jindal, V. Sekar, B. Sinopoli , “A control-theoretic approach for dynamic adaptive video streaming over HTTP,” in 2015 ACM Conference on Special Interest Group on Data Communication, Larnaca, Cyprus, Jul. 2015, pp. 325-338. doi: 10.1109/ISCC.2015.7405532.
[19]	C. Zhou ,C.-W. Lin, X. G. Zhang, and Z. M. Guo, “A control-theoretic approach to rate adaption for DASH over multiple content distribution servers,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 24, no.4, Apr. 2014. doi: 10.1109/TCSVT.2013.2290580.
[20]	E. C. R .Mok, X. Luo, and R. Chang, “QDASH: a QoE-aware DASH system,” in Proc. ACM Multimedia Syst., Chapel Hill, USA, Feb. 2012, pp. 11-22. doi: 10.1145/2155555.2155558.

Adaptive Mobile Video Delivery Based on Fountain Codes and DASH: A Survey

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 20

Related Articles 4

Recommended Articles

Metrics

[1]	GAO Nianzhen, YU Yifang, HUA Xinhai, FENG Fangzheng, JIANG Tao. A Content-Aware Bitrate Selection Method Using Multi-Step Prediction for 360-Degree Video Streaming [J]. ZTE Communications, 2022, 20(4): 96-109.
[2]	Christian Timmerer, Anatoliy Zabrovskiy. Automating QoS and QoE Evaluation of HTTP Adaptive Streaming Systems [J]. ZTE Communications, 2019, 17(1): 18-24.
[3]	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.
[4]	Yiling Xu, Shaowei Xie, Hao Chen, Le Yang, Jun Sun. DASH and MMT and Their Applications in ATSC 3.0 [J]. ZTE Communications, 2016, 14(1): 39-49.