Queuing analysis with traffic models based on deterministic dynamical systems

Measurements of communication traffic from a wide variety of sources have suggested that correlations persist in such sources over fairly long time scales. This has called into question the use of traditional traffic models for the performance analysis of such networks, and has sparked an interest in studying novel kinds of traffic models. In particular, a suggestion has been made to build models based on expanding deterministic dynamical systems. Deterministic dynamical systems can exhibit chaotic behavior, which has many of the features of statistical behavior, and can indeed be studied rigorously using probabilistic techniques. We make some remarks regarding the analysis of queues driven by such traffic models.