Modeling multimedia traffic is an important issue in performance analysis and design of communication networks. With introduction of new applications, the characteristics of data traffic changes. In this paper, a measurement study of ATM Network traffic has been carried out and it is shown that the recorded data exhibit self-similar features. The conclusions are supported by a comprehensive analysis using one of the most popular statistical methods called Indices of Dispersion. Our results validate one of the most striking findings of the present teletraffic research: a broad range of packet network traffic has fractal-like behavior. We also investigate three popular synthetic self-similar traffic models and find out the most accurate one for the measured traffic.
A Model of Self-Similar Data Traffic Applied to Ethernet Traces
