A prediction algorithm for real-time video traffic based on wavelet packet

Abstract

Long-term prediction is a key problem in real-time video traffic applications. Most of real-time video traffic belong to VBR traffic and has specific properties such as time variation, non-linearity and long range dependence. In this paper, feature extraction method of real-time video traffic based on multiscale wavelet packet decomposition is proposed. On this basis, LMS algorithm is adopted to predict wavelet coefficients. Through reverse wavelet transforms of the predicted wavelet coefficients, the long-term prediction of real-time video traffic is realized. Numerical and simulation results show that this long-term prediction algorithm can accurately track the variation trend of video signal and obtain an excellent prediction result. © Springer-Verlag Berlin Heidelberg 2013.