Dette er studietilbudet for studieår 2019-2020. Endringer kan komme.

This course first introduces Petri net theory; then, the theory is used for modeling, simulation and performance analysis of discrete event systems.

Learning outcome

After completing the course, the student shall:
  • Understand what performance evaluation and simulation means when many computers are connected in a system
  • Make models of realistic systems and run simulations on the models.
  • Apply Petri nets for advanced mathematical modeling of discrete event systems.
  • Use Applied Statistical techniques for filtering and analysis of data.


Introduction to quantitative methods for construction, dimensioning, and analysis of distributed systems; performance analysis for systems development and maintenance; basic concepts, measurement techniques, and tools for performance analysis; Petri net theory; discrete event based models with GPenSIM; applied statistical techniques (like factor analysis, ANOVA, hypothesis testing) for filtering and analysis of data.

Required prerequisite knowledge



Written exam and assignment(s)
Weight Duration Mark Supporting materials
Written exam40/1004 hoursA - FNo printed or written materials are allowed. Approved basic calculator allowed.
Project work60/100 A - FAll.

Course teacher(s)

Course coordinator
Reggie Davidrajuh
Head of Department
Tom Ryen

Method of work

4 hours lectures and 2 hours exercises.

Overlapping courses

Course Reduction (credits)
Discrete Simulation and Performance Analysis (MID280_1) 10

Open to

Master studies at the Faculty of Science and Technology.

Course assessment

Form and/or discussion.


Hruz,B. and Zhou,M.C. (2007) Modeling and Control of Discrete-event Dynamic Systems. Springer Verlag.

Dette er studietilbudet for studieår 2019-2020. Endringer kan komme.

Last updated: 24.01.2020