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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.

Contents

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

None.

Exam

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.

Literature

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: 10.12.2019