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> Study at Esisar > Engineering degree in Embedded Systems

- 3AMMA332

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  • Number of hours

    • Lectures : 13.5
    • Tutorials : 12.0
    • Laboratory works : -
    • Projects : -
    • Internship : -
    • Written tests : -
    ECTS : 2.5
  • Officials : Laurent LEFEVRE

Goals

  • To be able to build stochastic models with Poisson process, Markov chains and queues
  • To be able to identify Markovian processes and analyze its main characterizations and performance indexes
  • To be able to understand Kendall notations, build queues models and analyze the global performances of a network of Markovian queues

Content

  1. Poisson Process
  2. Discrete time Markov chains
  3. Coninuous time Markov chains
  4. Queuing theory: elementary queues
  5. Queuing theory: networks

Prerequisites

Any undergraduate courses in:

  1. linear algebra (including matrix computation and analysis)
  2. probability (including discrete and continuous laws and convergence theorems)

Tests



Calendar

The course exists in the following branches:

see the course schedule for 2021-2022

Additional Information

Course ID : 3AMMA332
Course language(s): FR

The course is attached to the following structures:

  • Team Mathematics for engineers

You can find this course among all other courses.

Bibliography

  • Queuing networks and Markov chains, Gunter BOLCH, Stefan GREINER, Hermann DE MEER and Kishor S. TRIVEDI, Wiley, 2006 (second edition)
  • Théorie des files d'attente, des chaînes de Markov aux réseaux à forme produit. Bruno BAYNAT, Hermes, 2000
  • Processus stochastiques. Dominique FOATA et Aimé FUCHS, Dunod, 2002
  • Processus de Markov et applications, Etienne Pardoux, Dunod, 2007

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Date of update June 25, 2015

Université Grenoble Alpes