Markov Chains (ePub)
Theory and Applications
(Sprache: Englisch)
Markov chains are a fundamental class of stochastic processes.
They are widely used to solve problems in a large number of domains
such as operational research, computer science, communication
networks and manufacturing systems. The success of Markov...
They are widely used to solve problems in a large number of domains
such as operational research, computer science, communication
networks and manufacturing systems. The success of Markov...
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Markov chains are a fundamental class of stochastic processes.
They are widely used to solve problems in a large number of domains
such as operational research, computer science, communication
networks and manufacturing systems. The success of Markov chains is
mainly due to their simplicity of use, the large number of
available theoretical results and the quality of algorithms
developed for the numerical evaluation of many metrics of
interest.
The author presents the theory of both discrete-time and
continuous-time homogeneous Markov chains. He carefully examines
the explosion phenomenon, the Kolmogorov equations, the convergence
to equilibrium and the passage time distributions to a state and to
a subset of states. These results are applied to birth-and-death
processes. He then proposes a detailed study of the uniformization
technique by means of Banach algebra. This technique is used for
the transient analysis of several queuing systems.
Contents
1. Discrete-Time Markov Chains
2. Continuous-Time Markov Chains
3. Birth-and-Death Processes
4. Uniformization
5. Queues
About the Authors
Bruno Sericola is a Senior Research Scientist at Inria Rennes
- Bretagne Atlantique in France. His main research activity
is in performance evaluation of computer and communication systems,
dependability analysis of fault-tolerant systems and stochastic
models.
They are widely used to solve problems in a large number of domains
such as operational research, computer science, communication
networks and manufacturing systems. The success of Markov chains is
mainly due to their simplicity of use, the large number of
available theoretical results and the quality of algorithms
developed for the numerical evaluation of many metrics of
interest.
The author presents the theory of both discrete-time and
continuous-time homogeneous Markov chains. He carefully examines
the explosion phenomenon, the Kolmogorov equations, the convergence
to equilibrium and the passage time distributions to a state and to
a subset of states. These results are applied to birth-and-death
processes. He then proposes a detailed study of the uniformization
technique by means of Banach algebra. This technique is used for
the transient analysis of several queuing systems.
Contents
1. Discrete-Time Markov Chains
2. Continuous-Time Markov Chains
3. Birth-and-Death Processes
4. Uniformization
5. Queues
About the Authors
Bruno Sericola is a Senior Research Scientist at Inria Rennes
- Bretagne Atlantique in France. His main research activity
is in performance evaluation of computer and communication systems,
dependability analysis of fault-tolerant systems and stochastic
models.
Autoren-Porträt von Bruno Sericola
Bruno Sericola is a senior Research Scientist at Inria Rennes - Bretagne Atlantique in France. His main research activity is in performance evaluation of computer and communication systems, dependability analysis of fault-tolerant systems and stochastic models.
Bibliographische Angaben
- Autor: Bruno Sericola
- 2013, 1. Auflage, 410 Seiten, Englisch
- Verlag: John Wiley & Sons
- ISBN-10: 1118731530
- ISBN-13: 9781118731536
- Erscheinungsdatum: 05.08.2013
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- Dateiformat: ePub
- Grösse: 19 MB
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Sprache:
Englisch
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