TCP tra c is multifractal : a numerical study

The apparent`fractal' properties of TCP data traac have recently attracted considerable interest. Most prominently, fractional Brownian motion (FBM) has been used to model the long range dependence of traac traces through self-similarity. Traac being by nature a process of positive increments, though, a multifractal approach appears more natural. In this study, various traces of TCP traac have been analyzed from both points of view. Though evidence for statistical self-similarity is present in certainàspects' of the traac, the multifractal scaling behavior is much more convincing. Furthermore, crucial LAN speciic characteristics of data traac are revealed by the multifractal analysis (MA) only. TCP traac at Berkeley and at CNET, e.g., looks entirely diierent from a multifractal point of view while showing about the same self-similarity parameter H. As a further example, MA suggests that L evy stable motion is in certain situations a more accurate model than FBM. In conclusion, to consider traac traces as multifractal random measures rather than as (monofractal) self-similar processes is not only more natural but has also various numerical advantages. A novel approach to queueing supports this conclusion.