基于ARIMA模型的网络流量预测

:网络流量预测在网络规划、流量管理等方面起着重要的作用,是业务管理的主要研究内容之一。在分析研究网络流量实测数据的基础上,建立了网络流量预测的ARIMA模型,该模型较之传统的Poisson过程、Markov过程等随机模型,能更好地描述Internet多构性、突发连续性和自相似性等特征。在模型定阶之后,运用改进的线性建模方法推导确定了模型参数。给出了不同预测步数条件下的流量预测数据,并和流量实测值进行了对比实验。实验结果表明,该模型在预测步数较小(l<3)的情况下,预测误差在5%左右。

Network Traffic Prediction based on ARIMA Model

As one of the main contents of service management, traffic prediction plays an important role in network layout, traffic management etc. A network traffic prediction model is proposed based on ARIMA model after studying on real data collected from CERNET. The model is better than traditional Poisson, Markov and other models for it's more suitable for describing the characters of Internet. The parameters of the model are educed by using improved linear modeling. Traffic prediction data under different conditions is compared with real data, and the experiment results show that the prediction error is about 5%.