The syllabus consists of introduction to system, modeling and simulation of different types of systems, including modeling, validation, verification, analysis of simulation output, queuing theory, random number generation, and study of simulation languages.
Understand the concept of simulation and modeling of real-time systems
System and System Environment, Components of System, Discrete and Continuous Systems, 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 Computer, 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 Queuing Systems, Measurement of Queueing System Performance, Elementary idea about networks of Queuing with emphasis to computer systems, Applications of Queuing Systems
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 of real-time systems (continuous and discrete event systems)Simulation of Queuing SystemsRandom Number GenerationStudy of Simulation Tools and Languages