SFARIMA: A New Network Traffic Prediction Algorithm

In this paper, we have studied on network traffic self-similarity as a starting point, analyze and predict data of the real network traffic by Fractal Autoregressive Integrated Moving Average (FARIMA), and propose sliding FARIMA (SFARIMA) network traffic prediction model. The model keeps sliding the time sequence to compensate the time lag of FARIMA and reduce the fitting error, therefore, it matches the original self-similar sequence better.

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