At the end of this lecture, a student should be able to
demonstrate theoretical results in stochastic process theory,
solve modeling problems,
develop equations for measuring the performance of stochastic processes while formally justifying the approach,
use simulation to observe a theoretical or applied result concerning Markov processes, renewal processes, and queues,
Our objective is to help students to understand and to solve random processes that may encounter in communication systems.
We give theory of renewal and Markov processes and basics of queueing theory,
We highlight the algorithmic and implementational aspects of the specification model. We will highlight algorithmic aspects of discrete-event simulation technics. Langage of use is R exclusively.
The lecture is organized only if enough students decide to follow it.
Lectures (30h), accompanied by exercise sessions (15h)
Written exam.
S. Resnick. Adventures in Stochastic Processes. Birkhäuse, 2005.
I. Adan et J. Resing. Queueing Theory. Available on line, Netherlands, 2002
H. Kobayashi et B.L. Mark. System Modeling and Analysis. Fondations of System Performance Evaluation. Pearson, 2009.
Lawrence M. Leemis and Stephen K. Park, Discrete-Event Simulation: A First Course, Prentice Hall, 2006.
| Training | Study programme | Block | Credits | Mandatory |
|---|---|---|---|---|
| Master in Computer Science | Standard | 1 | 5 | No |
| Master in Computer Science | Finalité spécialisée en data science | 2 | 5 | No |
| Master in Computer Science | Finalité spécialisée en software engineering | 2 | 5 | No |