Recent analyses of real data/internet traffic indicate that data traffic exhibits long-range dependence as well as self-similar or multi-fractal properties. By using mathematical models of Internet traffic that share these properties we can perform analytical studies of network traffic. This gives us an opportunity to analyse potential bottlenecks and estimate delays in the networks. Processes with multi-fractal properties can be modeled by multiplying the output of Markov Modulated Rate Processes (MMRP) [1] each defined by four parameters. The MMRP are easily used in stochastic fluid flow modeling. This model is also suited for analysis of other traffic types e.g. VoIP and thus, it allows for integration of different traffic types, i.e. time-sensitive voice traffic with best-effort data traffic. Using this model we can calculate performance parameters for each individual stream that enters the system/model. In this paper we show how to construct a multi-fractal process that is matched to measured data from MMRP sub processes.

Vi försöker matcha parametrar som hör till processer med multifraktala egenskaper. Vi försöker matcha mot verklig trafik.