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Titlebook: Introduction to Queuing Theory; B. V. Gnedenko,I. N. Kovalenko Book 1989Latest edition Springer Science+Business Media New York 1989 Appro

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Introduction to the First Edition,s, stores, automatic machines, etc.) gave rise to interesting, new mathematical problems. These problems dealt primarily with questions of priority service to telephone subscribers, regulation of inventory in stores to ensure an uninterrupted supply to customers, and determination of an adequate num
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Problems of Queueing Theory under the Simplest Assumptions,rs arriving at a queueing system. Thus, in order to calculate particle loss in a counter, we must know how the particles enter the counters. Similarly, when the operation of a telephone exchange is implemented, we must take into account the special features of the stream of subscriber-to-exchange ca
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The Study of the Incoming Customer Stream,e discussed simple streams, which until recently played the central role in queueing theory. From the viewpoint of a probabilist the simple stream is, although very important, only a particular type of discrete stochastic process. It also has recently become evident that in practical applications th
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Some Classes of Stochastic Processes,e of systems can be described by Markov processes with finitely or denumerably many states. However, Markov processes involve maximal analytical assumptions: both arrivals of new customers and completion of servicing customers that are in the system should not depend on previous history. There is no
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Semi-Markov Models of Queueing Systems,ing, etc.) as well as the analytical assumptions concerning the incoming stream of customers and the distribution of service time. The classification proposed by Kendall is the one commonly used. Many authors extended this classification [see, e.g., Borovkov’s book (1972)]. For our purposes Kendall’
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Statistical Simulation of Systems,ms. To apply this method, a “source of randomness” is required, i.e., a device that produces realizations of random numbers. Such devices are called . (RNG). RNG generate a sequence {.}, which is viewed as a sequence of independent random variables with a given distribution. Usually uniform random n
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Introduction to the Second Edition,on and operations research). Along with Markovian methods, powerful ergodic methods have been developed and a stability theory of service systems has been worked out. The method of statistical simulation has become one of the most widespread computational tools for solving problems of queueing theory.
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