Network Traffic Predicting Based on Wavelet Transform and Autoregressive Model
基于小波变换与自回归模型的网络流量预测

Network traffic prediction based on wavelet transform and autoregressive model is proposed. The original discrete series consisting of network traffic data is decomposed into approximate series and several detail series. The result of single branch reconstruction of each decomposed series is more unitary than the original series in frequency, and it can be built traffic model with autoregressive model. The prediction of the original series can be obtained by the synthesis of each reconstructed series prediction result. As shown in a set of experiments, the novel method is of higher accuracy in comparison with the traditional ones.