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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 multi-scale 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 realtime 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.