# system modelling and simulation

Semester : VI

Course Code : 18CS645

CIE Marks : 40 SEE Marks : 60

- System Software And Compilers
- computer graphics and visualization
- Web Technology And Its Applications
- data mining and data warehousing
- object oriented modelling and design
- cloud computing and its applications
- advanced JAVA and J2EE
- system modelling and simulation
- mobile application development
- introduction to DATA structures and algorithm
- programming in JAVA
- Introduction to operating system

## SYSTEM MODELLING AND SIMULATION

18CS645

#### SYLLABUS

### Module-1

**Introduction:** When the simulation is the appropriate tool and when it is not appropriate, Advantages and disadvantages of Simulation; Areas of application, Systems and system environment; Components of a system; Discrete and continuous systems, Model of a system; Types of Models, Discrete-Event System Simulation Simulation examples: Simulation of queuing systems. **General Principles.****Textbook 1: Ch. 1, 2, 3.1.1, 3.1.3**

### Module-2

**Statistical Models in Simulation: **Review of terminology and concepts, Useful statistical models, Discrete distributions. Continuous distributions, Poisson process, Empirical distributions. **Queuing Models:** Characteristics of queuing systems, Queuing notation, Long-run measures of performance of queuing systems, Long-run measures of performance of queuing systems cont…, Steady-state behaviour of M/G/1 queue, Networks of queues,**Textbook 1: Ch. 5,6.1 to 6.3, 6.4.1,6.6**

### Module-3

**Random-number generation:** Properties of random numbers; Generation of pseudo-random numbers, Techniques for generating random numbers, Tests for Random Numbers, **Random-Variate Generation:** Inverse transform technique Acceptance-Rejection technique.**Textbook 1: Ch. 7,8.1, 8.2 **

### Module-4

**Input Modeling:** Data Collection; Identifying the distribution with data, Parameter estimation, Goodness of Fit Tests, Fitting a non-stationary Poisson process, Selecting input models without data, Multivariate and Time-Series input models.**Estimation of Absolute Performance:** Types of simulations with respect to output analysis, Stochastic nature of output data, Measures of performance and their estimation, Contd.**Textbook 1: Ch. 9, 11.1 to 11.3**

### Module-5

Measures of performance and their estimation, Output analysis for terminating simulations Continued.., Output analysis for steady-state simulations.**Verification, Calibration And Validation: Optimization:** Model building, verification and validation, Verification of simulation models, Verification of simulation models, Calibration and validation of models, Optimization via Simulation.**Textbook 1: Ch. 11.4, 11.5, 10**

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