Neural network based approach for MPEG video traffic prediction

Abstract

In the near future, video is going to be the major Internet traffic and the most popular standard used to transport and view video is MPEG. The MPEG traffic is VBR (variable bit rate) traffic & in the form of a time-series representing frame/VOP (video object planes) sizes. Video traffic prediction and modeling is important in enhancing the reliable operation over these networks. In this paper, the MPEG-4 VBR video traffic is predicted by ANN (Artificial Neural Network). The arm is to predict the future frame of video stream. In single frame prediction problem, the information of previous frame sizes is used to predict the next frame size of the sequence. As a tool for the prediction, we use neural network - multilayer perception feed forward neural network. (FMLP). The prediction results of neural network have compared with the traditional averaging method. The results show that the neural approach is best as compared to averaging approach.