37760 - Systems Simulation

Academic Year 2017/2018

  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Computer Science (cod. 8028)

Learning outcomes

At the end of the course students will have acquired methods and tools to design, implement and validate simulation models for the performance analysis and assessment of computer and communication systems and for the analysis of social systems. Students will be able to design, implement and validate simulation models for the analysis and assessment of complex systems.

Course contents

1. classification of systems and models;

2. design of simulation experiments;

3. design and implementation of simulators;

4. random number generation and random variate generation;

5. techniques for discrete event simulation;

6. input and output data analysis;

7. verification, validation and testing of simulation model;

8. simulation tools;

9. parallel and distributed simulation;

10. introduction to agent based simulation;

11. analysis and evaluation of complex systems.

12. Introduction to Virtual Reality.

Readings/Bibliography

- M. Law, W. D. Kelton. Simulation Modeling and Analysis, McGraw-Hill, 2000.

- R. M. Fujimoto. Parallel and Distributed Simulation Systems, Wiley Interscience, 2000.

- Jerry Banks, John S. Carson, II,Barry L. Nelson, David M. Nicol. Discrete-Event System Simulation, 5/E, Prentice Hall, 2010.  

- Christos G. Cassandras, S. Lafortune. Introduction to Discrete Event Systems, Springer, 2006.

- Macal, C., and M. J. North. 2009. Agent-based modeling and simulation. In Proceedings of the 2009 Winter Simulation Conference, ed. M. D. Rossetti, R. R. Hill, B. Johansson, A. Dunkin, and R. G. Ingalls.

- Steven M. LaValle. Virtual Reality, Cambridge University Press, 2017

Teaching methods

classroom lectures, practical exercises, project.

Assessment methods

The final assessment consists of the development of simulation projects and an oral examination  Each part of the assessment is passed if the student scores at least 18/30 in it. The final score is based on the scores the student has obtained in the oral examination and the project.

Teaching tools


All course material (lecture slides, exercises and other resources) will be made available on the course web page. 

Links to further information

http://www.cs.unibo.it/~donat/

Office hours

See the website of Lorenzo Donatiello