Applied Probability and Queues Theory
An introduction to queueing theory, and the first comprehensive account of new developments in the subject in the past decade. Provides a thorough treatment of Markov processes, renewal theory, regenerative processes and random walks, and discusses in some detail basic models including the GI/G/1 queue, risk processes, and dams. Particular attention has been given to modern probabilistic points of view, as alternatives to traditional analytic methods--but the choice of topics is traditional. Exercises included for key chapters. Survey of mathematical prerequisites given in an appendix. Illustrated.
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MARKOV JUMP PROCESSES
QUEUEING THEORY AT THE MARKOVIAN
General birthdeath processes
17 other sections not shown
according apply approximation argument arrival assume becomes bounded called Chapter clear clearly Consider continuous convergence Corollary corresponding customers cycle define denote density discrete distribution easily equation equivalent ergodic evaluate example exists exponential expression fact finite follows formula function further given Hence holds identically immediately implies independent infinite initial integrable intensity irreducible jump Lemma limit Markov chain matrix mean measure method Notes obtained obvious occur particular period Poisson positive recurrent possible present probability Problems Proof Proposition prove queue queue length random walk recurrent references regenerative renewal process renewal theorem respect result satisfies seen server Show solution space standard stationary stationary distribution Statistics sufficient Suppose Theorem theory transition unique waiting yields zero