Network Traffic Prediction Based on Wavelet Transform and Season ARIMA Model

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NETL

外文摘要：To deal with the characteristic of network traffic， a prediction algorithm based on wavelet transform and Season ARIMA model is introduced in this paper。 The complex correlation structure of the network history traffic is exploited with wavelet method 。For the traffic series under different time scale， self-similarity is analyzed and different prediction model is selected for predicting。 The result series is reconstructed with wavelet method。 Simulation results show that the proposed method can achieve higher prediction accuracy rather than single prediction model。

外文关键词：

network trafficwaveletseason arima

作者：

Yongtao Wei、Jinkuan Wang、Cuirong Wang

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作者单位：

School of Information Science and Engineering, Northeastern University,Shenyang, China

会议名称：

International symposium on neural networks;ISNN 2011

会议地点：

Guilin(CN);Guilin(CN)

会议母体文献：

Advances in neural networks - ISNN 2011

页码：

p.152-159

出版时间：

2011