Osais Computer Simulation

A Foundational Approach using Python
1. Auflage 2017
ISBN: 978-1-4987-2683-2
Verlag: CRC Press
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 314 Seiten

Reihe: Chapman & Hall/CRC Computer and Information Science Series

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.

Typically, simulation involves two key steps: modeling and implementation. In this book, these processes are divided to minimize confusion and help introductory students grasp the transition to stochastic simulation. Modeling is covered in the first half of each chapter and is presented with event graphs and design of experiments. Then, as a tool of choice for scientists and engineers, Python programs are used throughout the book to help students implement their knowledge. The chapters are aided by a heavy use of Illustrations, and many examples are provided to re-enforce the concepts presented. The book also features a full chapter of case studies, as well as real working code, encouraging students to compare results obtained from simulation with those obtained using analytical methods. Additionally, most of the necessary mathematics is abstracted by procedures that show how the mathematical techniques can be implemented in the real world. This helps make the shift from models to programs straightforward.

Some other features of this book are:

- Simulation programs are divided into two distinct components: simulator and model.

- Both simulation without an event list and with an event list are covered.

- The single-queue single-server queuing system is used as a running example throughout the book

- A complete chapter on the Monte Carlo method and variance-reduction techniques are included.

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.

Autoren/Hrsg.

Osais, Yahya Esmail

Fachgebiete

• Mathematik | Informatik EDV | Informatik Technische Informatik
• Mathematik | Informatik Mathematik Mathematik Allgemein

Inhaltsverzeichnis

PART I THE FUNDAMENTALS

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

PART II MANAGING COMPLEXITY

7 Event Graphs

What Is an Event Graph?

Examples

Translating Event Graphs Into Code

8 Building Simulation Programs

Timedriven Simulation

Eventdriven Simulation

Writing Eventdriven Simulation Programs

Programming Issues

PART III PROBLEM-SOLVING

9 The Monte Carlo Method

Estimating the Value of

Numerical Integration

Estimating a Probability

Variance Reduction Techniques

PART IV SOURCES OF RANDOMNESS

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

PART V CASE STUDIES

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

Über Autor(innen)

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.