Markov-Modulated On–Off Processes in IP Traffic Modeling

This paper deals with the modeling of real IP flows using Markov-modulated On–Off processes. In first section paper, we summarize knowledge found so far about Markov modulated regular process model, which has already been published in our previous papers. For sake completeness, also well-known facts regarding Bernoulli process. second section, deal continuation Our own derivation hitherto-unknown probability distribution time spaces (tail distribution) is completely new. its derivation, used tail generating function, and then, calculated moments (mean, variation, third initial moment). will allow us to create a new numerical procedure for estimating MMBP parameters from measured traffic. Finally, present formula sizing network resources given flow effective bandwidth respect QoS based on level