MPEG-4 Bandwidth Prediction for Broadband Cable Networks

In this paper, we analyze the bandwidth requirements of MPEG-4 and propose and evaluate the accuracy of two new MPEG-4 video traffic models. The first predicts the size of the B-frame while the second predicts the size of the group of pictures (GOP). In a broadband cable network, the B-frame prediction model can be employed by a cable headend to provision video bandwidth efficiently or more importantly, reduce bit rate variability and bandwidth requirements via selective B-frame dropping, thereby minimizing buffering requirements and packet losses at the set top box. It will be shown that the model provides highly accurate prediction for a wide variety of video types, in particular, high action and regular movies encoded in high quality resolution. This is an important benefit since high motion MPEG videos demand the highest bandwidth and generate the widest range of bit rate requirements. Although the B-frame prediction model is very simple to implement, this paper also proposes two methods to simplify its operation further without sacrificing prediction accuracy. We then enhance the B-frame and GOP prediction models using a new scene change detector metric.