Models of Asymptotic
نویسنده
چکیده
A class of nonhomogeneous Markov systems with hierarchic state space working in diierent scales of time (slow and fast) that are adequate mathematical models at the analysis and modelling of various classes of computing systems and networks of a complex stochastic structure is studied. Models of asymptotic decreasing dimension and enlargement (merging) of state space are considered. Applications to approximative analytic modelling of queue-ing systems with hierarchic state space switched by some Markov environment are investigated.
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