Course

Discrete Simulation and Performance Analysis (DAT530)

Facts

Course code DAT530

Credits (ECTS) 10

Semester tution start Autumn

Language of instruction English

Number of semesters 1

Exam semester Autumn

Time table View course schedule

Literature Search for literature in Leganto

Introduction

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

Content

Note! This is an elective course and may be cancelled if fewer than 10 students are enrolled by August 20 for the autumn semester/January 20 for the spring semester. 

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)

Weight 1/1

Duration 4 Hours

Marks Letter grades

Aid No printed or written materials are allowed. Approved basic calculator allowed

Written exam

Weight 40/100

Duration 4 Hours

Marks Letter grades

Aid No printed or written materials are allowed. Approved basic calculator allowed

Project work

Weight 60/100

Marks Letter grades

Aid 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).

Written exam counts 40 % of total grade. Exam with pen and paper.

Both project and exam must be passed to get a final grade in the course.

Method of work

4 hours lectures and 2 hours exercises.

Open for

Admission to Single Courses at Master Level at the Faculty of Science and Technology
Data Science City and Regional Planning - Master of Science Degree Programme, Five Years Computational Engineering Computer Science Industrial Economics Industrial Automation and Signal Processing - Master's Degree Programme - 5 year Robot Technology and Signal Processing - Master's Degree Programme Structural and Mechanical Engineering Petroleum Engineering Master's Degree Programme in Societal Safety, Specialisation in Technical Societal Safety
Exchange programme at The Faculty of Science and Technology

Admission requirements

Must meet the admission requirements of one of the study programmes the course is open for.

Course assessment

The faculty decides whether early dialogue will be held in all courses or in selected groups of courses. The aim is to collect student feedback for improvements during the semester. In addition, a digital course evaluation must be conducted at least every three years to gather students’ experiences.

Contact

Head of Department:
Tom Ryen
Course coordinator:
Reggie Davidrajuh

Offered by

Faculty of Science and Technology

Department of Electrical Engineering and Computer Science

The course description is retrieved from FS (Felles studentsystem). Version 1