Prerequisites for Participation

Bachelor level knowledge and basic skills in probability theory.

Intended Learning Outcomes

Students who have successfully finished this module

• understand why models are so important;
• have a better understanding of how to accurately model a system;
• have good ideas on what kind of models are useful and what kind of techniques can be used to solve these models;
• have acquired advance knowledge in Markov Chain and Queuing theories;
• have manipulated discrete even simulation.

Content

The objective of this course is to introduce students to the problem of modeling and performance evaluation of systems. It aims at answering the following questions: Why models are important? When do we need to evaluate the performance of a system? How? What kind of models and techniques are useful?
This course will present both analytical modeling (Markov chain, queuing theory) and simulation. Example of application will mainly concern, but will not be restricted to, communication networks and computer systems.

Course topics:

• Performance evaluation of systems
• Modeling
• Communication networks
• Computer systems
• Analysis
• Markov chains
• Queuing theory
• Discrete event simulation
• Generalities
• NS (Network Simulator)

Teaching and Learning Methods

• 2h weekly hours lecture
• 4h weekly hours integrated interactive tutorials (problem solving, assignments discussion, lab sessions)

Assessment and Grading Procedures

There will be a mid-term exam in the middle of the course that is worth 20% of the final course grade, a simulation project that is also worth 20% and a final exam that will count 60% for the final grade. A makeup exam will be organized for those who failed the first session.

Workload calculation (contact hours, homework, exam preparation,..)

• 6h weekly contact hours x 10 weeks = 60 h
• 6h weekly hours preparation and afterwork x 10 weeks = 60 h
• Exams preparation: 30 h
• Total: 150 h

Frequency and dates

Offered every Spring semester:

• Classes start mid-January and end mid-April.
• Mid-semester exam around beginning of March
• Final exam at the beginning of May.
• Makeup exam for those who failed the first session in June.

Max. Number of Participants

30

Enrolment Procedures

Request to the head of CNI program

Recommended Reading, Course Material

• Baynat B., Théorie des files d’attente, des chaînes de Markov aux réseaux à forme produit, Hermes Science Publications, 2000.
• Bolch G., Greiner S., de Meer H. et Trivedi K.S., Queueing Networks and Markov Chain, John Wiley, 2006.
• Ross S.M., Introduction to Probability Models, 12th edition, Academic Press, 2019.
• Stewart W.J., ‪Probability, Markov Chains, Queues, and Simulation: ‪The Mathematical Basis of Performance Modeling, Princeton University Press, 2009.