37760 - Systems Simulation

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. analytical models: queueing systems and queueing networks;

3. design of simulation experiments;

4. random number generation and random variate generation;

5. discrete events simulazione techniques;

6.  agent based simulation;

7.  simulation and machine learning;

8. digital twin;

9. design and implementation of simulators and simulation tools;

10. input and output data analysis of simulation models;

11. verification, validation and testing of simulation models;

12. introduction to parallel and distributed simulation;

13. analysis and evaluation of complex systems.

14. Introduction to Virtual Reality.

Readings/Bibliography

- M. Law, W. D. Kelton. Simulation Modellino and Analysis, McGraw-Hill, 2015.

- 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, 2013.

- Christos G. Cassandras, S. Lafortune. Introduction to Discrete Events Systems, Springer, 2021.

- 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.

- A. Sharma, E. Kosasih, J. Zhang, A. Brintrup, A. Calinescu. Digital Twins: State of the art theory and pratice, challenges, and open research questions. In Journal of Industrial Infromation Integration, vol 30, 2022, https://doi.org/10.1016/j.jii.2022.100383.

- Steven M. LaValle. Virtual Reality, Cambridge University Press, 2023

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/

Links to further information

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

Office hours

See the website of Lorenzo Donatiello