analysis of rate-distortion functions and congestion control in scalable internet video streaming
Internet streaming applications usually have strict requirements on bandwidth, delay, and packet loss, while the current best-effort Internet does not provide any Quality-of-Service (QoS) guarantees to end flows. To achieve a higher level of QoS for the end user, Fine-granular Scalability (FGS), which has both strong error-resilience and flexibility during streaming over variable-bandwidth channels, has been accepted as a standard coding scheme for the video streaming profile in MPEG-4 [19]. Note that FGS and its extensions (e.g., progressive FGS) can also be used in the emerging video coding standards such as H.26L. This paper investigates rate-distortion (R-D) models of FGS coders and shows how such models can be used in a simple rate control framework for FGS streaming over the Internet. In terms of congestion control, we examine advantages and drawbacks of Kelly's proportional-fairness framework [12] and investigate its practical use both in the best-effort and AQM-enabled Internet. Our simulation results show that the developed R-D models provide fundamental insight into the structure of FGS coders and that constant-quality streaming is possible as long as the number of end flows competing at each bottleneck resource remains fairly stationary.
congestion control video streaming r-d modeling scalable coding mpeg-4 fgs