Supporting Real Time VBR Video Using Dynamic Reservation Based on Linear Prediction

Abstract

A dynamic bandwidth allocation strategy to support variable bit rate (VBR) video traffic is proposed. This strategy predicts the bandwidth requirements for future frames using either adaptive or non-adaptive least mean square (LMS) error linear predictors. The adaptive technique does not require any prior knowledge of the statistics, nor assumes stationarity. Several reservation schemes and pro-active congestion approach are also presented. Analysis using half hour long video traces indicate the prediction errors for the bandwidth required for the next frame are almost white noise.

By reserving bandwidth equal to the predicted value, only the prediction errors need to be buffered. Because the errors are almost white noise, small buffers size, can achieve high utilizations and small delay. Simulation results show that for the same expected cell loss, buffers size is reduced by more than a factor of 100 and network utilization increased of more that 250% as compared to the traditional fixed service rate.