Systems Simulation

Learning Outcomes

he course presents simulation techniques with particular emphasis on discrete event simulation and applications in computer computational systems and communication networks.

Upon successful completion of the course, the students will be in position to:

• design system models with the required details level that serves better the problem at hand
• develop simulation programs in general purpose programming language (e.g C++) to simulate and evaluate the behavior of simpler systems
• use more sophisticated simulation software for the study and performance evaluation of more complex communication networks and computational systems (e.g network simulator ns3 and CloudSim for cloud computing systems)
• design experiments, collect measurements and interpret and evaluate simulation results

Course Contents

• Introduction to dynamic discrete event systems.
• Development of discrete system models, event-advance design, time-advance design, activity-based design.
• Pseudorandom number generation, random variables generation.
• Overview of simulation languages and platforms.
• Development of simulation programs using general purpose programming languages.
• Measurement techniques, traffic load and experiment design.
• Statistical analysis of simulation experiments, transient and steady state, data collection, confidence intervals, variation reduction techniques.
• Simulation exercises and examples of data networks and cloud computing systems. Theoretical results verification.

Recommended Readings

1. Roumeliotis and Souravlas, “Simulation Techniques”, Epikentro Publications.
2. Kouikoglou and Konstantas, “Simulation of Discrete Event Systems”, Disigma Publications, 2016.
3. Harry Perros, “Computer Simulation Techniques – The Definitive Introduction”, free download from https://people.engr.ncsu.edu/hp/files/simulation.pdf
4. Averill M. Law and W. David Kelton, “Simulation Modeling and Analysis”, McGraw-Hill, Inc.
5. NS manual and tutorials, https://www.nsnam.org/documentation/