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Springer - Regeneration and Networks of Queues: 3 (Applied Probability)

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Description

Networks of queues are essential models for understanding a wide variety of congestion phenomena. In many real-world scenarios, discrete event simulation is the only way to study the behavior of complex networks. This often presents a challenge because many simulations are non-Markovian, meaning the underlying stochastic process cannot be represented as a continuous time Markov chain with a countable state space. This book from the Applied Probability series by Springer provides a solution by representing the underlying stochastic process of the simulation as a generalized semi-Markov process. It focuses on developing the necessary probabilistic and statistical methods required for the discrete event simulation of networks of queues. This resource is designed for those needing rigorous mathematical frameworks to analyze complex systems where traditional Markovian models fall short.

Key Features

Provides mathematical methods for the discrete event simulation of networks of queues.

Addresses non-Markovian simulations where traditional continuous time Markov chains are not applicable.

Uses the representation of underlying stochastic processes as generalized semi-Markov processes.

Offers tools to study complex networks through the lens of congestion phenomena.

Part of the Applied Probability series from Springer for academic and professional use.

Product Specifications

Format
paperback
Domain
Amazon UK
Publication Date
05 November 2012
Listed Since
14 July 2013

Barcode

No barcode data available

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