Prediction-based admission control using FARIMA models

The FARIMA (p,d,q) model is a good traffic model capable of capturing both the long-range and short-range behavior of a network traffic stream in time. In this paper, we propose a prediction-based admission control algorithm for an integrated service packet network. We suggest a method to simplify the FARIMA model fitting procedure and hence to reduce the time of traffic modeling and prediction. Our feasibility-study experiments showed that FARIMA models which have number of parameters could be used to model and predict actual traffic on quite a large time scale.