Criteria to design chaotic self-similar traffic generators

A self-similar behavior characterizes the traffic in many real-world commun ication networks. This traffic is traditionally modeled as an ON/OFF discre te-time second-order selfsimilar random process. The self-similar processes are identified by means of a polynomially decaying trend of the autocovari ance function. In this work we concentrate en two criteria to build a chaot ic system able to generate self-similar trajectories. The first criterion r elates self-similarity with the polynomially decaying trend of the autocova riance function. The second one relates self-similarity with the heavy-tail ed ness of the distributions of the sojourn times in the ON and/or OFF stat es. A family of discrete-time chaotic systems is then devised among the cou ntable piecewise affine Pseudo-Markov maps. These maps can be constructed s o that the quantization of their trajectories emulates traffic processes wi th different Hurst parameters and average load. Some simulations are report ed showing how, according to the theory, the map design is able to fit thos e specifications.