Simulation is a controlled statistical sampling technique that can be used to study complex stochastic systems when analytic and/or numerical techniques do not suffice. The focus of this book is on simulations of discrete-event stochastic systems; namely, simulations in which stochastic state transitions occur only at an increasing sequence of random times. The discussion emphasizes simulations on a finite or countably infinite state space.

* Develops probabilistic methods for simulation of discrete-event stochastic systems
* Emphasizes stochastic modeling and estimation procedures...

Networks of queues arise frequently as models for a wide variety of congestion phenomena. Discrete event simulation is often the only available means for studying the behavior of complex networks and many such simulations are non Markovian in the sense that the underlying stochastic process cannot be repre sented as a continuous time Markov chain with countable state space. Based on representation of the underlying stochastic process of the simulation as a gen eralized semi-Markov process, this book develops probabilistic and statistical methods for discrete event simulation of networks of...

Networks of queues arise frequently as models for a wide variety of congestion phenomena. Discrete event simulation is often the only available means for studying the behavior of complex networks and many such simulations are non- Markovian in the sense that the underlying stochastic process cannot be repre- sented as a continuous time Markov chain with countable state space. Based on representation of the underlying stochastic process of the simulation as a gen- eralized semi-Markov process, this book develops probabilistic and statistical methods for discrete event simulation of networks of...