Bsc Csit Nepal

Simulation and Modeling

Course Description:

The syllabus consists of introduction to system, 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 concept of queuing theory, random number generation as well as study of some simulation languages.

Course Objectives:

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

    Concept of system and system environment

  • Components of System

    System, entities, attributes, events, state variables and other terms related to system

  • Discrete and Continuous System

    Introduction and examples

  • System Simulation, Model of a System, Types of Model

    Introduction to system simulation and system model, different types of models and examples (physical/ mathematical, static/dynamic, discrete/continuous, deterministic/stochastic)

  • Use of Differential and Partial differential equations in Modelling

    Brief review of how differential and partial differential equations can be used in system- modelling

  • Advantages, Disadvantages and Limitations of Simulation, Application Areas

    Advantages, Disadvantages, Limitations and Applications of system simulation

  • Phases in Simulation Study

    Study of different phases during simulation

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

  • Continuous System Models Analog Computer, Analog Methods, Hybrid Simulation, Digital-Analog Simulators, Feedback Systems

    Concept, examples, use of differential equations for modelling continuous system

  • Discrete Event Simulation, Representation of time, Simulation Clock and Time Management

    Concept of discrete event simulation, time representation and management

  • Arrival Processes - Poisson Processes, Non-stationary Poisson Processes, Batch Arrivals

    Concept of arrival pattern, generation of arrival pattern using Poisson and Non-stationary Poisson with example, Introduction to batch arrival processes

  • Models of Gathering statistics

    Different statistics (like counts, summary measures, utilization, occupancy, distributions etc) that are needed to generate report and methods to gather such statistics

  • Probability and Monte Carlo Simulation

    Concept with an example

Unit 3: Queuing System (6 Hrs.)

  • Characteristics and Structure of Basic Queuing System, Models of Queuing System

    Concept of Basic Queuing System, Its Characteristics, Discipline, Models and related terms

  • Queuing notation

    Kendall’s notation for queuing system

  • Single server and Multiple server Queuing Systems

    Concept and examples of single server and multiple server queue

  • Measurement of Queuing System Performance, Elementary idea about networks of Queuing with particular emphasis to computer system

    Performance evaluation of queuing system (M/M/1) in terms of parameters like average number of customers, average time spent in system and in queue per customer, server utilization, cost of waiting time and idle time, with numerical examples

  • Elementary idea about network of queuing with particular emphasis to computer system

    Introduction of network of queues

  • Applications of queuing system

    Examples of computer system related queuing systems and other applications of queuing system

Unit 4: Markov Chains (2 Hrs.)

  • Features, Process Examples, Applications

    Concept, Features, Examples, Applications of Markov Chains

Unit 5: Random Numbers (7 Hrs.)

  • Random Numbers and its properties, Pseudo Random Numbers

    Concept, properties and types of random numbers

  • Methods of generation of Random Number

    Linear Congruential Method (mixed and multiplicative), Mid square method

  • Tests for Randomness - Uniformity and independence

    • Uniformity testing – K-S Test and Chi – square test
    • Independent testing – Gap test, Auto correlation test, Poker test upto 4 digits
  • Random Variate Generation

    Random variate generation via inverse transform technique and acceptance-rejection technique

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

    Concept of Model Building; verification; validation and calibration; three step approach, Introduction to accreditation of models

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

  • Confidence Intervals and Hypothesis Testing, Estimation Methods (Point Estimation and confidence interval with examples), Simulation run statistics, Replication of runs, Elimination of initial bias

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

  • Simulation Tools
  • Simulation Languages - GPSS
    • study and use of language with related problem
    • study of different blocks of GPSS blocks
    • concept of queue, storage, facility, multi-server queue, decision making
  • Case Studies of different types of Simulation Models, Construction of sample mathematical models

Laboratory Work:

After completing this course, students should have practical knowledge regarding simulation of some real time systems (continuous and discrete event systems), Queuing Systems, Random Number generations as well as study of Simulation Tools and Language. Verification and validation of models can be done, the analysis of outputs produced in the laboratory exercise 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

Text Books:

  1. Jerry Banks, John S. Carson, Barry L. Nelson, David M. Nicole, “Discrete Event system simulation”, 5th Edition, Pearson Education

Reference Books:

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