Multimedia Tools and Applications

, Volume 40, Issue 1, pp 111–134 | Cite as

Video streaming over the internet with optimal bandwidth resource allocation

Article

Abstract

In this paper, an adaptive framework for video streaming over the Internet is presented. The framework is a joint design of packet scheduling and rate control with optimal bandwidth resource allocation. The transmission rate is dynamically adjusted to obtain maximal utilization of the client buffer and minimal allocation of the bandwidth. Under the constraint of the transmission rate, a prioritized packet scheduling is designed to provide a better visual quality of video frames. The packet scheduling is a refined bandwidth allocation which takes into account of varying importance of the different packets in a compressed video stream. Moreover, the proposed approach is scalable with increasing multimedia flows in the distributed Internet environment. Comparisons are made with the most current streaming approaches to evaluate the performance of the framework using the H.264 video codec. The extensive simulation results show that the average Peak Signal to Noise Ratio (PSNR) increases in our proposed approach. It provides a better quality of the decoded frames, and the quality of the decoded frames changes more smoothly. The achieved video quality among different users also has a lower fluctuation, which indicates a fair sharing of network resources.

Keywords

Video streaming Quality of service Optimal bandwidth allocation Congestion control 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bajic IV, Tickoo O, Kalyanaraman AS, Woods JW (2003) Integrated end-to-end buffer management and congestion control for scalable video communications. In: IEEE ICIP’03, Barcelona, September 2003, pp 257–260Google Scholar
  2. 2.
    Balk A, Gerla M, Maggiorini D, Sanadidi MY (2004) Adaptive video streaming: pre-encoded MPEG-4 with bandwidth scaling. Comput Networks 44(4):415–439CrossRefGoogle Scholar
  3. 3.
    Bansal D, Balakrishnan H (2001) Binomial congestion control algorithms. In: Proceedings of the IEEE INFOCOM’01, Anchorage, pp 631–640Google Scholar
  4. 4.
    Bouras C, Gkamas A, Karaliotas A, Stamos K (2004) Architecture and performance evaluation for redundant multicast transmission supporting adaptive QoS. J Multimedia Tools Appl 25(1):85–110CrossRefGoogle Scholar
  5. 5.
    Cai L, Shen X, Pan J, Mark JW (2005) Performance analysis of TCP-friendly AIMD algorithms for multimedia applications. IEEE Trans Multimedia 7(2):339–353CrossRefGoogle Scholar
  6. 6.
    Chen I-R, Li S-T, Yen I-L (2005) Adaptive QoS control based on benefit optimization for video servers providing differentiated services. J Multimedia Tools Appl 25(2):167–185CrossRefGoogle Scholar
  7. 7.
    Chen S-C, Shyu M-L, Gray I, Luo H (2005) An adaptive rate-control streaming mechanism with optimal buffer utilization. J Syst Softw 75(3):271–282 (special issue on adaptive multimedia computing)CrossRefGoogle Scholar
  8. 8.
    Chou P, Miao Z (2006) Rate-distortion optimized streaming of packetized media. IEEE Trans Multimedia 8(2):390–404CrossRefGoogle Scholar
  9. 9.
    Cuetos P, Ross K (2003) Optimal streaming of layered video: joint scheduling and error concealment. In: Proceedings of the eleventh ACM international conference on Multimedia, Berkeley, CA, pp 55–64Google Scholar
  10. 10.
    Dong J, He C, Zheng YF, Ewing RL (2005) AVP: a highly efficient transport protocol for low bit rate multimedia communications. J Multimedia Tools Appl 25(2):187–216CrossRefGoogle Scholar
  11. 11.
    Floyd S, Handley M, Padhye JM, Widmer J (2000) Equation-based congestion control for unicast applications. In: Proceedings of ACM SIGCOMM, Stockholm, August 2000, pp 43–56Google Scholar
  12. 12.
    Jin S, Guo L, Matta I, Bestavros A (2003) A spectrum of TCP-friendly widow-based congestion control algorithms. IEEE/ACM Trans Netw 11(3):341–355CrossRefGoogle Scholar
  13. 13.
    Kang SH, Zakhor A (2003) Effective bandwidth based scheduling for streaming multimedia. In: Proceedings of ICIP, Barcelona, September 2003, pp 633–636Google Scholar
  14. 14.
    Kim Y-G, Kim J, Kuo C-CJ (2004) TCP-friendly internet video with smooth and fast rate adaptation and network-aware error control. IEEE Trans Circuits Syst Video Technol 4(2): 256–268CrossRefGoogle Scholar
  15. 15.
    Krasic C, Walpole J, Feng W (2003) Quality-adaptive media streaming by priority drop. In: NOSSDAV. Monterey, June 2003, pp 112–121Google Scholar
  16. 16.
    Kusmierek E, Du DHC (2005) Streaming video delivery over internet with adaptive end-to-end QoS. J Syst Softw 75(3):237–252CrossRefMathSciNetGoogle Scholar
  17. 17.
    Luo H, Shyu M-L, Chen S-C (2005) A multi-buffer scheduling scheme for video streaming. In: Proceedings of the IEEE international conference on multimedia and expo (ICME), Amsterdam, 6–8 July 2005, pp 1218–1221Google Scholar
  18. 18.
    Luo H, Shyu M-L, Chen S-C (2006) An optimal resource utilization scheme with end-to-end congestion control for continuous media stream transmission. Comput Networks 50(7):921–937CrossRefGoogle Scholar
  19. 19.
    Mielke M, Aygun R, Song Y, Zhang A (2002) Plus: probe-loss utilization streaming mechanism for distributed multimedia presentation systems. IEEE Trans Multimedia 4(4):561–577CrossRefGoogle Scholar
  20. 20.
    Joint Video Team of ISO/IEC MPEG and ITU-T VCEG (2002) Joint model number 1, revision 1 (JM-1R1)Google Scholar
  21. 21.
    Rejaie R, Handley M, Estrin D (1999) RAP: an end-to-end rate-based congestion control mechanism for realtime streams in the internet. In: Proceedings of INFOCOM 99, New York, March 1999, pp 1337–1345Google Scholar
  22. 22.
    Rhee I, Xu L (2005) Limitations in equation-based congestion control. In: Proceedings of ACM SIGCOMM. Philadelphia, PA, August 2005, pp 49–60Google Scholar
  23. 23.
    Tunali ET, Kantarci A, Ozbek N (2005) Robust quality adaptation for internet video streaming. J Multimedia Tools Appl 27(3):431–448CrossRefGoogle Scholar
  24. 24.
    Vieron J, Guillemot C (2004) Real-time constrained TCP-compatible rate control for video over the internet. IEEE Trans Multimedia 6(3):634–646CrossRefGoogle Scholar
  25. 25.
    Wang B, Kurose JF, Sheony PJ, Towsley DF (2004) Multimedia streaming via TCP. In: ACM Multimedia, New York City, NY, October 2004, pp 908–915Google Scholar
  26. 26.
    Widmer J, Denda R, Mauve M (2001) A survey on TCP-friendly congestion control. IEEE Netw 15(3):28–37CrossRefGoogle Scholar
  27. 27.
    Wu D, Hou YT, Zhang Y-Q (2000) Transporting real-time video over the internet: challenges and approaches. Proc IEEE 88(12):1855–1877CrossRefGoogle Scholar
  28. 28.
    Zhang Q, Zhu W, Zhang YQ (2001) Resource allocation for multimedia streaming over the internet. IEEE Trans Multimedia 3(3):339–355CrossRefGoogle Scholar
  29. 29.
    Zhu P, Zeng W, Li C (2007) Joint design of source rate control and QoS aware congestion control for video streaming over the internet. IEEE Trans Multimedia 9(2):366–376CrossRefGoogle Scholar
  30. 30.
    Ziviani A, Wolfinger BE, de Rezende JF, Duarte OCMB, Fdida S (2005) Joint adoption of QoS scheme for MPEG streams. J Multimedia Tools Appl 26(1):59–80CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.Department of Electrical and Computer Engineering TechnologyIndiana University - Purdue University Fort WayneFort WayneUSA
  2. 2.Department of Electrical and Computer EngineeringUniversity of MiamiCoral GablesUSA
  3. 3.Distributed Multimedia Information System Laboratory, School of Computing and Information SciencesFlorida International UniversityMiamiUSA

Personalised recommendations