A Stable Multifractal Model of Network Traffic and Its Verification

There have been two a priori models up till now concerning network traffic: self-similar and multifractal models. The self-similar model is simple enough to characterize network traffic with the single exponent H, however it can not thoroughly describe the contents. The multifractal model, which is more accurate, is not practical because it uses multifractal spectra as functions to represent signals. Therefore, on the basis of the framework of IDC theory, this paper proposes a stable multifractal model of network traffic. It is tested on several traces by using the method of wavelet transforms that the model fits traffic precisely in terms of both scale behaviors and marginal distributions. As a specific case of multifractal processes, this model, by estimations of four parameters, can specify the representation of the multifractal exponent.