Prediction of Network Flow Based on Wavelet Analysis and ARIMA Model

Jingfei Li, Lei Shen, Yongan Tong
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引用次数: 8

Abstract

Internet traffic analysis, models simulation and prediction play a very important part in the network management and design.Combining wavelet techniques and time-series ARIMA model, the establishment of a network traffic prediction model in this paper. First, time series of wavelet decomposition of flow to gets detail coefficients and approximation coefficients, On the details coefficients, applying the stationary series model, on the approximation coefficients ,applying difference method, then using the stationary series ARIMA model to predict. At last,applying the actual network traffic to verify the model, The results show that the model has higher prediction accuracy.
基于小波分析和ARIMA模型的网络流量预测
网络流量分析、模型仿真和预测在网络管理和设计中起着非常重要的作用。本文将小波技术与时间序列ARIMA模型相结合,建立了网络流量预测模型。首先对时间序列的流量进行小波分解得到细节系数和近似系数,在细节系数上应用平稳序列模型,在近似系数上应用差分法,然后利用平稳序列ARIMA模型进行预测。最后,应用实际网络流量对模型进行验证,结果表明该模型具有较高的预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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