- 8
- Units
- 30
- Lessons
- 6/6
- Labs
Model the world and run it forward: discrete-event simulation, random numbers, queuing theory, and validation.
What you'll learn
The key areas this subject covers, mapped to the official curriculum.
- Concepts of systems, models and simulation study methodology
- Continuous and discrete-event simulation techniques
- Queuing systems and Markov chain analysis
- Random number generation, testing and variate generation
- Verification, validation and output analysis
Course units
The structured path through this subject.
- 1
Introduction to Simulation
What models and simulation are, system concepts, and the steps of a simulation study.
4 topics · 4 lessons available
- 2
Simulation of Continuous and Discrete System
Distinguishing continuous and discrete models and how each is simulated.
4 topics · 4 lessons available
- 3
Queuing System
Components of queues, notation, and the analytic models used to predict performance.
4 topics · 4 lessons available
- 4
Markov Chains
Stochastic processes, the Markov property, and steady-state analysis.
3 topics · 3 lessons available
- 5
Random Numbers
Properties of random numbers, generators, statistical tests, and variate generation.
5 topics · 5 lessons available
- 6
Verification and Validation
Making sure the model is built right and that it represents the real system.
3 topics · 3 lessons available
- 7
Analysis of Simulation Output
Handling terminating and steady-state runs, confidence intervals, and input modeling.
4 topics · 4 lessons available
- 8
Simulation of Computer Systems
Applying simulation to CPUs, networks and workloads, and the software used.
3 topics · 3 lessons available
Subject details
- Code
- CSC-328
- Credit hours
- 3
- Semester
- Semester V
- Category
- systems