Discrete Simulation and Performance Analysis (DAT530)

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


Course description for study year 2023-2024. Please note that changes may occur.

Facts

Course code

DAT530

Version

1

Credits (ECTS)

10

Semester tution start

Autumn

Number of semesters

1

Exam semester

Autumn

Language of instruction

English

Content

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.

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.

Required prerequisite knowledge

None

Exam

Written exam and assignment(s)

Form of assessment Weight Duration Marks Aid
Written exam 40/100 4 Hours Letter grades No printed or written materials are allowed. Approved basic calculator allowed
Project work 60/100 Letter grades All

The course has a continous assessment.Project counts 60% of total grade. The project can be done individually or in groups of 2-3 students.If a student fails to deliver the project on time, then the student will be awarded a fail mark. If valid documentation is provided (e.g., medical certificate), then extended time can be given to complete the project.If a student fails the project, the student may take a new project with a new title the next time the course goes as usual. However, under exceptional circumstances, the course coordinator may allow the student to start a new project in the following semester (no need to wait for the next course start).Both project and exam must be passed to get a final grade in the course.

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 (SP)
Discrete Simulation and Performance Analysis (MID280_1) 10

Open for

Computer Science - Master of Science Degree Programme Industrial Automation and Signal Processing - Master's Degree Programme - 5 year Robot Technology and Signal Processing - Master's Degree Programme Exchange programme at Faculty of Science and Technology

Course assessment

There must be an early dialogue between the course coordinator, the student representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.

Literature

Search for literature in Leganto