Among other topics of interest it deals with establishing fundamental relations between asymptotic frequencies and averages, pathwise stability, and insensitivity. These results are utilized to establish useful performance measures. The intuitive deterministic approach of this book will give researchers, teachers, practitioners, and students better insights into many results in queueing theory. The simplicity and intuitive appeal of the arguments will make these results more accessible, with no sacrifice of mathematical rigor. Recent topics such as pathwise stability are also covered in this context. The book consistently takes the point of view of focusing on one sample path of a stochastic process.
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An important role is played by the factorial moment measures and their extensions is the mathematical expectation and is called the measure of intensity. A generalization of stochastic point processes are the so-called marked stochastic point processes, in which marks from some measurable space with. The service times in a queueing system can be regarded as marks. In the theory of stochastic point processes, an important role is played by relations connecting, in a special way, given conditional probabilities of distinct events Palm probabilities.
Limit theorems have been obtained for superposition summation , thinning out and other operations on sequences of stochastic point processes. Various generalizations of Poisson stochastic point processes are widely used in applications. References A. Khinchin, "Mathematical methods in the theory of queueing" , Griffin Translated from Russian  D. Cox, V. Kerstan, K. Matthes, J. Belyaev, "Elements of the general theory of point processes" Appendix to Russian translation of: H.
Leadbetter, Stationary and related stochastic processes, Wiley,  R. Liptser, A. Shiryaev, "Statistics of random processes" , II. Applications , Springer Translated from Russian .
Point Processes And Queues, Martingale Dynamics
Point Processes and Queues
Point processes and queues, martingale dynamics
Point Processes and Queues : Martingale Dynamics