March 2014
Intermediate to advanced
456 pages
14h 17m
English
Traffic as offered to a network is stochastic and described by stochastic processes. Similarly, nodes processing traffic are described by queues. The by far most important models of traffic are based on the Poisson distribution, which is discussed in some detail.
A large class of queues and networks can be treated by Markov chain analysis—at least in principle—but the state space grows very fast with system size. We show some fundamental results and an approximation method where evaluation by randomization is applied to a truncated state space.
The frequently used Erlang formulas are discussed with focus on computational issues and some generalizations are presented. Analysis of a simple two-stage ...
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