Analysis and modelling of YouTube traffic

Transactions on emerging telecommunications technologies

Volumn 23, Issue 4, 2012, Pages 360-377

  Ameigeiras, Pablo ^a   Ramos Munoz, Juan J ^a   Navarro Ortiz, Jorge ^a   Lopez Soler, J M ^a  

^a UNIVERSITY OF GRANADA   (Spain)

Author keywords

Progressive download; Progressive download traffic generation; YouTube; Youtube application flow control; Youtube data rate; YouTube traffic generation

Indexed keywords

BANDWIDTH; VIDEO CAMERAS;

APPLICATION LAYERS; AVAILABLE BANDWIDTH; BANDWIDTH AVAILABILITY; CUMULATIVE DENSITY FUNCTIONS; DATA RATES; ENCODING RATES; EXPERIMENTAL EVALUATION; GENERATION RATE; NETWORK CONGESTIONS; NETWORK DESIGN; PROGRESSIVE DOWNLOAD; RELATIVE ERRORS; TRAFFIC GENERATION; TRAFFIC TRACES; VIDEO CLIPS; VIDEO QUALITY; YOUTUBE;

WEBSITES;

EID: 84863697761     PISSN: 1124318X     EISSN: 15418251     Source Type: Journal    
DOI: 10.1002/ett.2546     Document Type: Article

References (35)

1. Cisco Corporation. Cisco Visual Networking Index: forecast and methodology, 2010-2015. White paper. [cited 2012 April 25]. Available from: http://www.cisco. com/en/US/solutions/xcollateral/ns341/ns525/ns537/ns 705/ns827/white-paper-c11-481360-ns827-Networking-Solutions-White-Paper. html.
2. Alexa Corporation. The top 500 sites on the web. [cited 2012 April 25]. Available from: http://www.alexa.com/topsites.
3. Cisco Corporation. Cisco Visual Networking Index: global mobile data traffic forecast update, 2011-2016. White paper. [cited 2012 April 25]. Available from: http://www.cisco.com/en/US/solutions/collateral/ns341/ns525/ ns537/ns705/ns827/white-paper-c11-520862.pdf.
4. Garapati N. Quality estimation of YouTube video service, Master Thesis, Blekinge Institute of Technology, Sweden, Feb. 2010.
5. Gill P, Arlitt M, Li Z, Mahanti A. YouTube traffic characterization: a view from the edge, In Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement, San Diego, 2007, DOI: 10.1145/1298306.1298310.
6. Matera F, Matteotti F, Pasquali P, Rea L, Tarantino A, Baroncini V, Del Prete G, Gaudino G. Comparison between objective and subjective measurements of quality of service over an Optical Wide Area network. European Transactions on Telecommunications 2008;19(3):233-245. DOI: 10.1002/ett.1189.
7. Finamore A, Mellia M, Munafo M, Rao SG. YouTube everywhere: impact of device and infrastructure synergies on user experience, In Proceedings of the 11th Annual Internet Measurement Conference (IMC'11), Berlin, Germany, November 2011;345-360.
8. Adobe Systems Incorporated. Adobe Flash Player. [cited 2012 April 25]. Available from: http://www.adobe.com/
9. Adobe Systems Incorporated. Video file format specification version 10.1. [cited 2012 April 25]. Available from: http://download.macromedia.com/f4v/ video-file-format-spec-v10-1.pdf.
10. YouTube-DL documentation. [cited 2012 April 25]. Available from: http://rg3.github.com/youtube-dl/documentation. html.
11. Youtube Corporation. YouTube APIs and tools. [cited 2012 April 25]. Available from: http://code. google.com/intl/en-US/apis/youtube/overview.html.
12. Staehle B, Hirth M, Pries R, Wamser F, Staehle D. YoMo: a Youtube application comfort monitoring tool. Technical Report 467, University of Würzburg, March 2010.
13. Red Iris. Red Iris Weathermap. [cited 2012 April 25]. Available from: http://www.rediris.es/conectividad/weathermap/.
14. Wireshark Corporation. Wireshark network protocol analyzer. [cited 2012 April 25]. Available from: http://www.wireshark.org/.
15. Softperfect Research. SoftPerfect bandwidth manager lite version for Windows. [cited 2012 April 27]. Available from: http://www.softperfect.com/ products/bandwidth/.
16. Inlet Media Corporation. FLVTool2-flash video and meta data manipulation. [cited 2012 April 25]. Available from: http://www.inlet-media.de/flvtool2/.
17. Characterization of trace sets T1 and T2. [cited 2012 April 25]. Available from: http://dtstc.ugr.es/tl/downloads/set-t1-t2.csv.
18. Zhou J, Li Y, Adhikari VK, Zhang Z. Counting YouTube videos via random prefix sampling, In Proceedings of the 2011 Internet Measurement Conference (IMC'11), Berlin, Germany, 2011, DOI: 10.1145/2068816.2068851.
19. Google Data API Protocol - API query parameters. [cited 2012 April 25]. Available from: http://code. google.xcom/apis/youtube/2.0/developers-guide- protocol-api-query-parameters.html.
20. Characterization of trace set T3. [cited 2012 April 25]. Available from: http://dtstc.ugr.es/tl/downloads/format-set-t3.xlsx
21. and http://dtstc.ugr.es/tl/downloads/metadata-set-t3.xlsx.
22. Characterization of trace set T4. [cited 2012 April 25]. Available from: http://dtstc.ugr.es/tl/downloads/format-set-t4.xlsx
23. and http://dtstc.ugr.es/tl/downloads/metadata-set-t4.xlsx.
24. Alcock S, Nelson R. Application flow control in Youtube video streams. ACM SIGCOMM Computer Communication Review 2011;41(2). DOI: 10.1145/1971162. 1971166.
25. Rao A, Lim Y, Barakat C, Legout A, Towsley D, Dabbous, W. Network characteristics of video streaming traffic, In Proceedings of the 7th International Conference on emerging Networking EXperiments and Technologies (CoNEXT), Tokyo, Japan, December 2011. http://dl.acm.org/citation. cfm?doid=2079296.2079321.
26. Microsoft Corporation. Windows Media Services features and benefits. [cited 2012 February 27]. Available from: http://www.microsoft.com/windows/ windowsmedia/forpros/serve/features.aspx.
27. Varsa V, Curcio I. Transparent end-to-end packet switched streaming service (PSS); RTP usage model (release 9). 3GPP TR 26.937 V9.0.0, 2009.
28. Microsoft Corporation. IIS Media Services. [cited 2012 February 27]. Available from: http://technet.microsoft.com/en-us/library/ee729229 (WS.10). aspx. June 10, 2010.
29. Welzl M. Network Congestion Control: Managing Internet Traffic. John Wiley & Sons: The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England, 2005.
30. Palkopoulou E, Merkle C, Schupke DA, Gruber CG, Kirstädter A. Traffic models for future backbone networks - a service-oriented approach. European Transactions on Telecommunications 2011;22(4):137-150. DOI: 10.1002/ett.1464.
31. Cheng X, Dale C, Liu J. Understanding the characteristics of Internet short video sharing: YouTube as a case study. Technical Report arXiv:0707.3670v1 [cs. NI], Cornell University, arXiv e-prints, 2007.
32. Cha M, Kwak H, Rodriguez P, Ahn Y, Moon S. I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system, In Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement, San Diego, 2007, DOI: 10.1145/1298306.1298309.
33. Zink M, Suh K, Gu Y, Kurose J. Characteristics of YouTube network traffic at a campus network - measurements, models, and implications. Computer Networks 2008;53:501-514. DOI: 10.1016/j.comnet.2008.09.022.
34. Plissonneau L, En-Najjary T, Urvoy-Keller G. Revisiting web traffic from a DSL provider perspective: the case of YouTube, In Proceedings of the 19th ITC Specialist Seminar 2008 on Network Usage and Traffic (ITC SS 19), Berlin, Germany, 2008.
35. Mori T, Kawahara R, Hasegawa H, Shimogawa S. Characterizing traffic flows originating from largescale video sharing services. In Proceedings of Traffic Monitoring and Analysis: Second International Workshop (TMA 2010). Springer: Zurich, Switzerland, 2010;17-31.