Simulation and Modeling Syllabus (CSC 317) – TU BSc CSIT 5th Semester

Tribhuvan University
Institute of Science and Technology
Bachelor of Science in Computer Science and Information Technology

Course Description: The syllabus consists of an introduction to systems, and modelling and simulation of different types of systems. It includes the modelling of systems, its validation, verification and analysis of simulation output. It comprises the concepts of queuing theory and random number generation, as well as a study of some simulation languages.

Course Objective: To make students understand the concept of simulation and modelling of real time systems.

Course Contents

Unit 1. Introduction to Simulation (6 Hrs.)

System and System Environment, Components of System, Discrete and Continuous System, System Simulation, Model of a System, Types of Model, Use of Differential and Partial Differential Equations in Modeling, Advantages, Disadvantages and Limitations of Simulation, Application Areas, Phases in Simulation Study

Unit 2. Simulation of Continuous and Discrete System (7 Hrs.)

• Continuous System Models, Analog Computers, Analog Methods, Hybrid Simulation, Digital-Analog Simulators, Feedback Systems
• Discrete Event Simulation, Representation of Time, Simulation Clock and Time Management, Models of Arrival Processes – Poisson Processes, Non-stationary Poisson Processes, Batch Arrivals; Gathering Statistics, Probability, and Monte Carlo Simulation

Unit 3. Queuing System (6 Hrs.)

Characteristics and Structure of Basic Queuing System, Models of Queuing System, Queuing Notation, Single Server and Multiple Server Queueing Systems, Measurement of Queueing System Performance, Elementary Idea about Networks of Queuing with particular emphasis on the Computer System, Applications of Queuing System

Unit 4. Markov Chains (2 Hrs.)

Features, Process Examples, Applications

Unit 5. Random Numbers (7 Hrs.)

Random Numbers and their Properties, Pseudo-Random Numbers, Methods of Generation of Random Numbers, Tests for Randomness – Uniformity and Independence, Random Variate Generation

Unit 6. Verification and Validation (4 Hrs.)

Design of Simulation Models, Verification of Simulation Models, Calibration and Validation of the Models, Three-Step Approach for Validation of Simulation Models, Accreditation of Models

Unit 7. Analysis of Simulation Output (4 Hrs.)

Confidence Intervals and Hypothesis Testing, Estimation Methods, Simulation Run Statistics, Replication of Runs, Elimination of Initial Bias

Unit 8. Simulation of Computer Systems (9 Hrs.)

Simulation Tools, Simulation Languages: GPSS, Case Studies of different types of Simulation Models and Construction of sample Mathematical Models

Laboratory Works

After completing this course, students should have practical knowledge regarding simulation of some real time systems (continuous and discrete event systems), queuing systems, and random number generation, as well as a study of simulation tools and languages. Verification and validation of models can be done, and the analysis of outputs produced in the laboratory exercises can also be performed. The laboratory work should include:

• Implement different methods of random number generation
• Simulating games of dice that generate discrete random variates, using random number generation
• Testing of random numbers (K-S and Chi-Square Test)
• Implementing applications of Monte Carlo methods
• Implement applications of Markov chains
• Simulation of a single queue server system
• GPSS models – queue, storage, facility, multi-server queue, decision making problems

Text Books

1. Jerry Banks, John S. Carson, Barry L. Nelson, David M. Nicol, “Discrete-Event System Simulation”, 5th Edition, Pearson Education

Reference Books

1. Geoffrey Gordon, “System Simulation”
2. Averill M. Law, “Simulation Modeling and Analysis”, 5th Edition, McGraw-Hill