QoE-Oriented Fairness Control for DASH Systems Based on the Hierarchical Structure of SVC Streams

1. Shenker, S.: Fundamental design issues for the future Internet. IEEE J. Sel. Areas Commun. 13(7), 1176–1188 (1995)

   Article  Google Scholar 

2. ISO/IEC 23009–1:2014, Information technology – Dynamic adaptive streaming over HTTP (DASH) – Part 1: Media presentation description and segment formats. http://standards.iso.org/ittf/PubliclyAvailableStandards/c065274_ISO_IEC_23009-1_2014.zip

3. Reichel, J., Schwarz, H., Wien, M., Vieron, J.: Joint Scalable Video Model 9 of ISO/IEC 14496–10:2005/AMD3 Scalable Video Coding. Joint Video Team (JVT), Docs. JVT-X202 (2007)

   Google Scholar 

4. Sieber, C., Hossfeld, T., Zinner, T., Tran-Gia, P., Timmerer, C.: Implementation and user-centric comparison of a novel adaptation logic for DASH with SVC. In: IFIP/IEEE International Symposium on Integrated Network Management, pp. 1318–1323. IEEE Press, Ghent (2013)

   Google Scholar 

5. Kalva, H., Adzic, V., Furht, B.: Comparing MPEG AVC and SVC for adaptive HTTP streaming. In: IEEE International Conference on Consumer Electronics, pp. 158–159. IEEE Press, Las Vegas (2012)

   Google Scholar 

6. Cermak, G., Pinson, M., Wolf, S.: The relationship among video quality, screen resolution, and bit rate. IEEE Trans. Broadcast. 57, 258–262 (2011)

   Article  Google Scholar 

7. Daronco, L.C., Roesler, V., Lima, J.V.: Subjective video quality assessment applied to scalable video coding and transmission instability. In: ACM Symposium on Applied Computing, pp. 1898–1904, ACM, New York (2010)

   Google Scholar 

8. Stockhammer, T.: Dynamic adaptive streaming over HTTP - Standards and design principles. In: Second Annual ACM Conference on Multimedia Systems, pp. 133–144. ACM, San Jose (2011)

   Google Scholar 

9. Akhshabi, S., Begen, A., Dovrolis, C.: An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP. In: Second Annual ACM Conference on Multimedia Systems, pp. 157–168. ACM, San Jose (2011)

   Google Scholar 

10. Huang, T.-Y., Handigol, N., Heller, B., McKeown, N., Johari, R.: Confused, timid, and unstable: picking a video streaming rate is hard. In: ACM Conference on Internet Measurement, pp. 225–238. ACM, Boston (2012)

    Google Scholar 

11. Tian, G., Liu, Y.: Towards agile and smooth video adaptation in dynamic HTTP streaming. In: 8th International Conference on Emerging Networking Experiments and Technologies, pp. 109–120. ACM, Nice (2012)

    Google Scholar 

12. Mok, R.K.P., Luo, X., Chan, E.W.W., Chang, R.K.C.: QDASH: a QoE-aware DASH system. In: 3rd Multimedia Systems Conference, pp. 11–22. ACM, Chapel Hill (2012)

    Google Scholar 

13. Jiang, J., Sekar, V., Zhang, H.: Improving fairness, efficiency, and stability in http-based adaptive video streaming with festive. IEEE/ACM Trans. Network. 22(1), 326–340 (2014)

    Article  Google Scholar 

14. Mansy, A., Ver Steeg, B., Ammar, M.: SABRE: a client based technique for mitigating the buffer bloat effect of adaptive video flows. In: 4th ACM Multimedia Systems Conference, pp. 214–225. ACM, Oslo (2013)

    Google Scholar 

15. Kelly, F.P.: Charging and rate control for elastic traffic. Eur. Trans. Telecommun. 8, 33–37 (1997)

    Article  Google Scholar 

16. Marbach, P.: Priority service and max-min fairness. IEEE/ACM Trans. Network. 11(10), 733–746 (2003)

    Article  Google Scholar 

17. Wang, W.-H., Palaniswami, M., Low, S.H.: Application-oriented flow control: fundamentals, algorithms and fairness. IEEE/ACM Trans. Network. 14(6), 1282–1291 (2006)

    Article  Google Scholar 

18. Yin, X., Jindal, A., Sekar, V., Sinopoli, B.: A control-theoretic approach for dynamic adaptive video streaming over HTTP. SIGCOMM Comput. Commun. Rev. 45(5), 325–338 (2015)

    Article  Google Scholar 

19. Unanue, I., Urteaga, I., Husemann, R., Del Ser, J., Roesler, V., Rodriguez, A., Sanchez, P.: A tutorial on H264/SVC scalable video conding and its tradeoof between quality, coding efficiency and performance. In: Lorente, J.D.S. (ed.) Recent Advances on Video Coding, Chap. 1. InTech, Rijeka (2011)

    Google Scholar 

20. Gupta, R., Pulipaka, A., Seeling, P., Karam, L.-J., Reisslein, M.: H.264 coarse grain scalable (CGS) and medium grain scalable (MGS) encoded video: a trace based traffic and quality evaluation. IEEE Trans. Broadcast. 58(3), 428–439 (2012)

    Article  Google Scholar 

21. Przylucki, S., Sierszeń, A.: Gradation of video quality in DASH services using the H264/SVC coding. Image Process. Commun. 20, 15–24 (2016)

    Google Scholar 

22. ITEC – Dynamic Adaptive Streaming over HTTP. http://www-itec.uni-klu.ac.at/dash/

23. Joint Scalable Video Model – reference software. http://www.hhi.fraunhofer.de/departments/video-coding-analytics/research-groups/image-video-coding/research-topics/svc-extension-of-h264avc/jsvm-reference-software.html

24. Georgopoulos, P., Elkhatib, Y., Broadbent, M., Mu, M., Race, N.: Towards network-wide QoE fairness using openflow-assisted adaptive video streaming. In: ACM SIGCOMM Workshop on Future Human-Centric Multimedia Networking, pp. 15–20. ACM, Hong Kong (2013)

    Google Scholar 

25. Dakin, R.J.: A tree-search algorithm for mixed integer programming problems. Comput. J. 8(3), 250–255 (1965)

    Article  MathSciNet  MATH  Google Scholar 

26. ONF: Open Networking Foundation Software-Defined Networking (SDN) Definition. https://www.opennetworking.org/sdn-resources/sdn-definition

27. Przylucki, S., Czerwinski, D.: The ability to ensure a fair distribution of network resources for video streaming services based on DASH standard. Studia Informatica 36(2), 73–82 (2015)

    Google Scholar 

28. Linux Foundation, OpenDaylight. https://www.opendaylight.org/lithium

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