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Chaînes de Markov et Simulation à événements discretsInformatique Fondamentale (STI)

FISEFISA STI Semester 7 Common Core Machine translation

Markov Chains and Discrete Event Simulation

Teaching unit Fundamental Computer Science · S07T_INF3  |  EC Code S07T_INF3-5
Course on Celene
8ECTS (EU)
1.5Coefficient
38:00Hours

Séquencement

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Learning objectives

  • Discover the modelling of random phenomena by Markov chains,
  • Learn the theory of queues.
  • Learning to model queues.
  • Presentation of some complex queue networks.
  • Performance evaluation of queue systems.

Prerequisites

ModuleTeaching unitSemester
Statistics and Random ProcessesMathematics and Computer Science 5S5

Program

  • Stochastic process,

  • Finished and homogeneous Markov chains in discreet time,

  • Study of Markov chains in discrete time: transient and asymptotic behaviour,

  • Markov chain continuous time,

  • Birth and death processes,

  • The queues,

  • The queue networks.

  • Definition of SED

  • EDS analysis techniques.

  • Modeling of Physical Systems

  • Software Systems Modelling

  • Mobile system modelling

  • Performance characterization and evaluation techniques

Assessment

  • Ongoing monitoring

References

  • Queueing Networks and Markov Chains : Modeling and Performance Evaluation with Computer Science Applications, 2nd Edition. Gunter Bolch, Stefan Greiner, Hermann de Meer, Kishor Shridharbhai Trivedi. ISBN: 978-0-471-56525-3 Hardcover
  • Modeling and Tools for Network Simulation Wehrle, Klaus, Günes, Mesut, Gross, James. Springer. ISBN: 978-3-642-12331-3