This practical and accessible text enables readers from engineering, business, operations research, public policy and computer science to analyze stochastic systems. Emphasizing the modeling of real-life situations with stochastic elements and analyzing the resulting stochastic model, it presents the major cases of useful stochastic processes-discrete and continuous time Markov chains, renewal processes, regenerative processes, and Markov regenerative processes. The author provides reader-friendly yet rigorous coverage. He follows a set pattern of development for each class of stochastic processes and introduces Markov chains before renewal processes, so that readers can begin modeling systems early. He demonstrates both numerical and analytical solution methods in detail and dedicates a separate chapter to queueing applications. Modeling and Analysis of Stochastic Systems includes numerous worked examples and exercises, conveniently categorized as modeling, computational, or conceptual and making difficult concepts easy to grasp. Taking a practical approach to working with stochastic models, this book helps readers to model and analyze the increasingly complex and interdependent systems made possible by recent advances.Model the behavior of this system by a CTMC by giving the stale space, rale matrix, and the rate diagram. 18. ... Otherwise, if the token pool is not empty, an incoming packet takes a token from the pool and is instantaneously transmitted.
|Title||:||Modeling and Analysis of Stochastic Systems|
|Author||:||Vidyadhar G. Kulkarni|
|Publisher||:||CRC Press - 1996-05-15|