Computer Simulation: A Foundational Approach Using Python, 1st Edition (Hardback) book cover

Computer Simulation

A Foundational Approach Using Python, 1st Edition

By Yahya Esmail Osais

Chapman and Hall/CRC

275 pages | 109 B/W Illus.

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pub: 2017-11-17
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Computer simulation is an effective and popular universal tool that can be applied to almost all disciplines. Requiring only basic knowledge of programming, mathematics, and probability theory, Computer Simulation: A Foundational Approach Using Python takes a hands-on approach to programming to introduce the fundamentals of computer simulation.

The main target of the book is computer science and engineering students who are interested mainly in directly applying the techniques to their research problems. The book will be of great interest to senior undergraduate and starting graduate students in the fields of computer science and engineering and industrial engineering.


"This book is highly recommended for a graduate course in modeling and simulation. It is also recommended for an introductory course in modeling and simulation for a senior undergraduate course. In addition, it can be a good reference for researchers, working engineers and scientists who work in modeling and simulation and optimization. It is a good addition to the field of modeling and simulation. I hope you will enjoy the book as much as I have enjoyed reviewing it."

—Mohammad S. Obaidat, Past President of the Society for Modeling and Simulation International, SCS, and Editor-in-Chief, International Journal of Communication Systems

Table of Contents


1 Introduction

The Pillars of Science And Engineering

Studying the Queueing Phenomenon

What Is Simulation?

Lifecycle of a Simulation Study

Advantages and Limitations of Simulation

Overview of the Book

2 Building Conceptual Models

What Is a Conceptual Model?

Elements of a Conceptual Model

The Singleserver Queueing System

State Diagrams

Actual Time Versus Simulated Time

3 Simulating Probabilities

Random Experiments and Events

What Is Probability?

Computing Probabilities

Probability as a Sample Mean

4 Simulating Random Variables and Stochastic Processes

What Are Random Variables?

Some Useful Random Variables

Stochastic Processes

Dynamic System Evolution

Simulating Queueing Processes

5 Simulating the SingleServer Queueing System

Simulation Model

Collecting Simulated Data

Performance Laws

Independent Simulation Runs

Transient And Steady Phases

6 Statistical Analysis of Simulated Data

Populations and Samples

Probability Distribution Of The Sample Mean

Confidence Intervals

Comparing Two System Designs


7 Event Graphs

What Is an Event Graph?


Translating Event Graphs Into Code

8 Building Simulation Programs

Timedriven Simulation

Eventdriven Simulation

Writing Eventdriven Simulation Programs

Programming Issues


9 The Monte Carlo Method

Estimating the Value of

Numerical Integration

Estimating a Probability

Variance Reduction Techniques


10 Random Variate Generation

The Inversion Method

The Rejection Method

The Composition Method

The Convolution Method

Specialized Methods

11 Random Number Generation

Pseudorandom Numbers

Characteristics of a Good Generator

Just Enough Number Thoery

The Linear Congruential Method

The Multiplicative Congruential Method

Linear Feedback Shift Registers

Statistical Testing of Rngs


12 Case Studies

Network Reliability

Packet Delivery Over a Wireless Channel

Simple Arq Protocol

Appendix A Overview of Python

Appendix B An ObjectOriented

Appendix C The ChiSquared

Appendix D The Distribution

About the Author

Yahya E. Osais is a faculty in the department of computer engineering at King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia. He obtained his B.Sc. and M.Sc. from the same department in 2000 and 2003, respectively. In 2010, he obtained his Ph.D. from the department of systems and computer engineering at Carleton university, Ontario, Canada. Dr. Osais regulary teaches a graduate course on computer simulation for students in the college of computer science and engineering at KFUPM. He also teaches courses on computer engineering design and web technologies. His current research interest includes stochastic modeling and simulation, cyberphysical systems, and Internet of things.

About the Series

Chapman & Hall/CRC Computer and Information Science Series

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Subject Categories

BISAC Subject Codes/Headings:
COMPUTERS / Programming / Games
COMPUTERS / Computer Engineering