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On the Influence of Network Impairments on YouTube Video Streaming

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Języki publikacji
EN
Abstrakty
EN
Video sharing services like YouTube have become very popular which consequently results in a drastic shift of the Internet traffic statistic. When transmitting video content over packet based networks, stringent quality of service (QoS) constraints must be met in order to provide the comparable level of quality to a traditional broadcast television. However, the packet transmission is influenced by delays and losses of data packets which can have devastating influence on the perceived quality of the video. Therefore, we conducted an experimental evaluation of HTTP based video transmission focusing on how they react to packet delay and loss. Through this analysis we investigated how long video playback is stalled and how often re-buffering events take place. Our analysis revealed threshold levels for the packet delay, packet losses and network throughput which should not be exceeded in order to preserve smooth video transmission.
Rocznik
Tom
Strony
83--90
Opis fizyczny
Bibliogr. 23 poz., rys., tab.
Twórcy
autor
autor
autor
Bibliografia
  • [1] “Global mobile data traffic forecast update, 2010002015”, Cisco Visual Networking Index. White Paper, Cisco, 2011.
  • [2] A. Rao, Y. S. Lim, C. Barakat, A. Legout, D. Towsley, and W. Dabbous, “Network characteristics of video streaming traffic”, in Proc. 7th Int. Conf. Emerg. Netw. Exper. Technol. CoNEXT 2011, Tokyo, Japan, 2011.
  • [3] S. Alcock and R. Nelson, “Application flow control in YouTube video streams”. ACM SIGCOMM Comp. Commun. Rev., vol. 41, no. 2, pp. 24–30, 2011.
  • [4] I. Hickson, “HTML5: a vocabulary and associated APIs for HTML and XHTML”, April 2010 [Online]. Available: http://www. w3.org/TR/html5/
  • [5] A. Finamore, M. Mellia, M. Munafo, R. Torres, and S. R. Rao, “YouTube everywhere: impact of device and infrastructure synergies on user experience”, Tech. Rep. 418, Purdue University, May 2011.
  • [6] S. Acharya and B. C Smith, “Experiment to characterize videos stored on the web”, in Proc. ACM/SPIE Multimedia Comput. Netw. MMCN 1997, vol. 3310, pp. 166–178, 1997.
  • [7] S. Acharya, B. Smith, and P. Parns,“Characterizing user access to video on the world wide web”, in Proc. ACM/SPIE Multimedia Comput. Netw. MMCN 2000, vol. 3969, pp. 130–141, 2000.
  • [8] R. Rejaie, M. Handley, and D. Estrin, “Quality adaptation for congestion controlled video playback over the internet”, SIGCOMM Comput. Commun. Rev., vol. 29, no. 4, pp. 189–200, 1999.
  • [9] S. Floyd, M. Handley, J. Padhye, and Jörg Widmer, “Equationbased congestion control for unicast applications”, SIGCOMM Comput. Commun. Rev., vol. 30, no. 4, pp. 43–56, 2000.
  • [10] P. Gill, M. Arlitt, Z. Li, and A. Mahanti, “Youtube traffic characterization: a view from the edge”. in Proc. 7th ACM SIGCOMM Conf. Internet Measur. IMC 2007, San Diego, CA, USA, 2007, pp. 15–28.
  • [11] M. Zink, K. Suh, Y. Gu, and J. Kurose, “Characteristics of YouTube network traffic at a campus network-measurements, models, and implications”, Computer Netw., vol. 53, no. 4, pp. 501–514, 2009.
  • [12] L. Plissonneau, T. En-Najjary, and G. Urvoy-Keller, “Revisiting web traffic from a DSL provider perspective: the case of YouTube”, in Proc. ITC Spec. Seminar Netw. Usage Traffic, Berlin, Germany, 2008.
  • [13] M. Cha, H. Kwak, P. Rodriguez, Y. Y Ahn, and S. Moon, “I tube, you tube, everybody tubes: analyzing the world’s largest user generated content video system”, in Proc. 7th ACM SIGCOMM Conf. Internet Measur. IMC 2007, San Diego, CA, USA, 2007, pp. 1–14, 2007.
  • [14] X. Cheng, C. Dale, and J. Liu, “Statistics and social network of YouTube videos”, in Proc. 16th Int. Worksh. Quality of Service IWQoS 2008, Enschede, The Netherlands, 2008, pp. 229–238.
  • [15] A. Abhari and M. Soraya, “Workload generation for YouTube”, Multimedia Tools and Appl., vol. 46, no. 1, pp. 91–118, 2010.
  • [16] D. K. Krishnappa, S. Khemmarat, and M. Zink, “Planet YouTube: global, measurement-based performance analysis of viewer;’s experience watching user generated videos”, in Proc. IEEE 36th Conf. Local Comp. Netw. LCN 2011, Bonn, Germany, 2011, pp. 948–956.
  • [17] S. Benno, J. O. Esteban, and I. Rimac, “Adaptive streaming: the network HAS to help”, Bell Labs Tech. J., vol. 16, no. 2, pp. 101–114, 2011.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BATA-0017-0010
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