On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
Time series models for internet traffic
INFOCOM'96 Proceedings of the Fifteenth annual joint conference of the IEEE computer and communications societies conference on The conference on computer communications - Volume 2
Wide-area Internet traffic patterns and characteristics
IEEE Network: The Magazine of Global Internetworking
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Traffic behavior in a large-scale network can be viewed as a complicated non-linear system, so it is very difficult to describe the long-term network traffic behavior in a large-scale network. In this paper, according to the non-linear character of network traffic, the time series of network traffic is decomposed into trend component, period component, mutation component and random component by different mathematical tools. So the complicated traffic can be modeled with these four simpler sub-series tools. In order to check the decomposed model, the long-term traffic behavior of the CERNET backbone network is analyzed by means of the decomposed network traffic. The results are compared with ARIMA model. According to autocorrelation function and predicting error function, compounded model can get higher error precision to describe the long-term traffic behavior.