Traffic prediction using FARIMA models

Previous traffic measurements have found the coexistence of both long-range and short-range dependence in network traffic. Therefore, models are required to predict traffic that has both long-range and short-range dependence. This paper provides a procedure to model and predict traffic using FARIMA (p,d,q) models. Our experiments illustrate that the FARIMA model is a good model and is capable of capturing the property of actual traffic. We provide guidelines to simplify the FARIMA model fitting procedure and thus to reduce the time of traffic modeling and prediction.

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