Video streaming over the internet with optimal bandwidth resource allocation
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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.
KeywordsVideo streaming Quality of service Optimal bandwidth allocation Congestion control
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- 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
- 3.Bansal D, Balakrishnan H (2001) Binomial congestion control algorithms. In: Proceedings of the IEEE INFOCOM’01, Anchorage, pp 631–640Google Scholar
- 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
- 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
- 13.Kang SH, Zakhor A (2003) Effective bandwidth based scheduling for streaming multimedia. In: Proceedings of ICIP, Barcelona, September 2003, pp 633–636Google Scholar
- 15.Krasic C, Walpole J, Feng W (2003) Quality-adaptive media streaming by priority drop. In: NOSSDAV. Monterey, June 2003, pp 112–121Google Scholar
- 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
- 20.Joint Video Team of ISO/IEC MPEG and ITU-T VCEG (2002) Joint model number 1, revision 1 (JM-1R1)Google Scholar
- 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.Rhee I, Xu L (2005) Limitations in equation-based congestion control. In: Proceedings of ACM SIGCOMM. Philadelphia, PA, August 2005, pp 49–60Google Scholar
- 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