Tribhuvan University
Institute of Science and Technology
Bachelor of Science in Computer Science and Information Technology
Semester: V
Course Title: Simulation and Modeling
Course No: CSC317
Full Marks: 60 + 20 + 20
Pass Marks: 24 + 8 + 8
Credit Hours: 3
Nature of Course: Theory + Lab
The syllabus consists of introduction to system, modeling, and simulation of different types of systems. It includes the modeling of systems, its validation, verification, and analysis of simulation output. It comprises the concept of queuing theory, random number generation, as well as the study of some simulation languages.
To make students understand the concept of simulation and modeling of real-time systems.
- 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
- 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
- Characteristics and Structure of Basic Queuing System
- Models of Queuing System
- Queuing Notation
- Single Server and Multiple Server Queueing Systems
- Measurement of Queuing System Performance
- Elementary Idea About Networks of Queuing with Particular Emphasis on Computer Systems
- Applications of Queuing Systems
- Features
- Process Examples
- Applications
- Random Numbers and their Properties
- Pseudo-Random Numbers
- Methods of Generation of Random Numbers
- Tests for Randomness - Uniformity and Independence
- Random Variate Generation
- 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
- Confidence Intervals and Hypothesis Testing
- Estimation Methods
- Simulation Run Statistics
- Replication of Runs
- Elimination of Initial Bias
- Simulation Tools
- Simulation Languages: GPSS
- Case Studies of Different Types of Simulation Models and Construction of Sample Mathematical Models
Practical should include the simulation of some real-time systems (continuous and discrete event systems), Queuing Systems, Random Number Generations, as well as the 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 variate, using random number generation
- Testing of random numbers (K-S and Chi Square Test)
- Implementing applications of Monte Carlo methods
- Implement applications of Markov’s chain
- Simulation of single queue server system
- GPSS models - queue, storage, facility, multi-server queue, decision-making problems
- Jerry Banks, John S. Carson, Barry L. Nelson, David M. Nicole, “Discrete Event System Simulation”, 5th Edition, Pearson Education
- Geoffrey Gordon: System Simulation
- Law, "Simulation Modeling and Analysis", 5th Edition, McGraw-Hill