Page 74 - DCAP601_SIMULATION_AND_MODELING

Simulation and Modelling Sandeep Kumar, Lovely Professional University

Notes Unit 5: Discrete System Simulation (II)

CONTENTS
Objectives
Introduction
5.1 Simulating Randomness

5.2 Random-number Generators
5.3 Generation of Random Numbers
5.4 Summary
5.5 Keywords
5.6 Self Assessment
5.7 Review Questions
5.8 Further Readings

Objectives

After studying this unit, you will be able to:

 Describe Simulating Randomness
 Explain Generation of Random Numbers

Introduction

To generate truly random numbers requires precise, accurate, and repeatable system
measurements of absolutely non-deterministic processes. In comparison with PRNGs, TRNGs
extract randomness from physical phenomena and introduce it into a computer. You can imagine
this as a die connected to a computer, but typically people use a physical phenomenon that is
easier to connect to a computer than a die.

5.1 Simulating Randomness

1. Stochastic Systems: Systems with intrinsic randomness or changeability in their behaviour.

(a) These systems with chance can be normal or man-made.
(b) Instances of systems where randomness is simulated are:
(i) Inventory System
(ii) Water Reservoir

(iii) Advent of customers in a store
(iv) Demand for telephone line at exchange
(v) Births and deaths in a population
(vi) Particle collision in a reactor

(vii) Appearance of an elevator on a given floor

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