Capturing the complete multifractal characteristics of network traffic

We propose a new multifractal traffic model for network traffic. The model is a combination of a multiplicative cascade with an independent lognormal process. We show that the model has all the important properties observed in data traffic including long-range dependence (LRD), multifractality and lognormality. We also demonstrate that the model is flexible enough to capture the complete multifractal characteristics of data traffic including both the scaling function and the moment factor. On the other hand, we argue that the model is simple from practical point of view having only three parameters. Practical applications for measured data traffic and validation of the model with queueing performance evaluation are also presented.