Page 148 - Proceedings of the 2017 ITU Kaleidoscope
P. 148
2017 ITU Kaleidoscope Academic Conference
system can be structured in such a way that it enables the [16] http://www.cse.unsw.edu.au/~cs9417ml/RL1/algorithms.html
server to engagemultiple clients at a time. [17]ITU-T Recommendation Series J, “Objective Perceptual
Multimedia Video Quality Measurement in the Presence of a
ACKNOWLEDGEMENT Full Reference”, document # J.247, August 2008.
[18] “DirectShow (Windows)”. [Online] Available at
The research paper work presented here is supported by the https://msdn.microsoft.com/enus/library/windows/desktop/dd
375454(v=vs.85).aspx.
University Grant Commission (UGC), Government of [19] http://jnetpcap.com/
India, New Delhi. We would like to thank the UGC for the [20] https://www.airtel.in/4g/index
financial support and permission to publish the outcome. [21] “HTML5 Speed Test”. [Online]. Availableat:
http://speedof.me.
REFERENCES
[1] Sandvine, “Global Internet Phenomena Report” 2016,
https://www.sandvine.com/trends/global-internet-
phenomena/
[2] Cisco Visual Networking Index: Forecast and Methodology,
2016–2021, Updated on June 7, 2017
[3] Cisco Visual Networking Index: Global Mobile Data Traffic
Forecast Update, 2016–2021 White Paper, Updated on Feb 7,
2017.
[4] Jiwoo Park and Kwangsue Chung, “Client-side Rate
Adaptation Scheme for HTTP Adaptive Streaming Based on
th
Playout Buffer Model”, The 30 International Conference on
Information Networking (ICOIN), pp.190-194, Jan. 2016.
[5] Jonathan Kua, Grenville Armitage, and Philip Branch “A
Survey of Rate Adaptation Techniques for Dynamic
Adaptive Streaming over HTTP”, IEEE Communications
Surveys and Tutorials, Issue no. 99, March 2017.
[6] Sangwook Kim, Dooyeol Yun and Kwangsue Chung, “Video
Quality Adaptation Scheme for Improving QoE in HTTP
th
Adaptive Streaming”,The 30 International Conference on
Information Networking (ICOIN),, pp.201-205, Jan. 2016.
[7] Sangwook Bae, Dahyun Jang, and KyoungSoo Park, “Why Is
HTTP Adaptive Streaming So Hard?”, Proc. of the 6 Asia-
th
Pacific Workshop on Systems (APSys '15), Tokyo, July 27 -
28, 2015.
[8] Li Yu, TammamTillo, and Jimin Xiao, “QoE-Driven
Dynamic Adaptive Video Streaming Strategy With Future
Information”, IEEE Transactions on Broadcasting, Issue 99,
pp 1-12, April 2017.
[9] Guibin Tian and Yong Liu (2015), “Towards Agile and
Smooth Video Adaptation in HTTP AdaptiveStreaming”,
IEEE/ACM Transactions On Networking, Sept 2015.
[10] Sergio Cicalò, NesrineChanguel, VelioTralli, BessemSayadi,
FrédéricFaucheux, and SylvaineKerboeuf “Improving
QoEand Fairness in HTTP Adaptive Streaming Over LTE
Network”, IEEE Trans. on Circuits and Systems for Video
Technology, Vol. 26, Issue: 12, pp. 2284 – 2298, Dec. 2016
[11] Yu-Lin Chient, Kate Ching-Ju Lin, and Ming-Syan Chen,
“Machine Learning Based Rate Adaptation with Elastic
Feature Selection For Http-Based Streaming”, Proc. of IEEE
International Conference on Multimedia and Expo (ICME),
Turin, Italy, 29 June-3 July 2015.
[12] Richard S. Sutton and Andrew G. Barto, “Reinforcement
Learning:An Introduction”, MIT PressCambridge,
Massachusetts, 2012.
[13] Virginia Martín, Julián Cabrera, and NarcisoGarcía,“Design,
optimization and evaluation of a Q-Learning HTTP Adaptive
Video Streaming Client”,IEEE Trans on Consumer
Electronics, Vol. 62, No. 4, pp.380-388, Nov. 2016.
[14] Stefan Winkler, “Video Quality Measurement Standards –
Current Status and Trends”, Proc. of 7 International
th
Conference on Information, Communications and Signal
Processing (ICICS), Macau, China, 8-10 Dec. 2009.
[15] ITU-T Recommendation series G, “Transmission systems
and media, digital systems and networks”, G.1070, 2012.
– 132 –