Synthetic self-similar traffic in computer networks simulation is of imperative significance for the capturing and reproducing of actual Internet data traffic behavior. A universally used procedure for generating self-similar traffic is achieved by aggregating On/Off sources where the active (On) and idle (Off) periods exhibit heavy tailed distributions. This work analyzes the balance between accuracy and computational efficiency in generating self-similar traffic and
presents important results that can be useful to parameterize existing heavy tailed distributions such as Pareto, Weibull
and Lognormal in a simulation analysis. Our results were obtained through the simulation of various scenarios and were evaluated by estimating the Hurst (H) parameter, which measures the self-similarity level, using several methods.
KEYWORDS: Internet, Signal attenuation, Computer simulations, Computer science, Signal processing, Analytical research, Wireless communications, Chemical elements, Standards development, Mobile communications
This work analyses and compares the performance of the recently proposed micro-mobility protocols HAWAII and Hierarchical MIP when submitted to several levels of traffic load and scenarios that effectively degrade the low packet loss feature of these protocols. Furthermore, it is shown that the use of differentiated services within a given domain infrastructure results in a considerable increase of performance for mobile nodes. The preferential treatment offered to such mobile nodes protects micro-mobility protocols traffic from the fluctuations of background traffic with losses only occurring as a result of handoff events.