José M. Garrido – författare

This work introduces the application of the Java programming language in discrete-event simulation. In addition, the fundamental concepts and practical simulation techniques for modelling different types of systems to study their general behaviour and their performance are introduced. The approaches applied are the process interaction approach to discrete-event simulation and object-oriented modelling. Java is used as the implementation language and UML as the modelling language. The first offers several advantages compared to C++, the most important being thread handling, graphical user interfaces (GUI), and Web computing. The second language, UML (Unified Modeling Language), is the standard notation used today for modelling systems as a collection of classes, class relationships, objects, and object behaviour. The book concentrates on object-oriented modelling and implementation aspects of simulation models using Java and practical simulation techniques. In addition, the book illustrates the dynamic behaviour of systems using the various simulation models as case studies.

This book introduces the fundamental concepts and practical simulation te- niques for modeling different aspects of operating systems to study their g- eral behavior and their performance. The approaches applied are obje- oriented modeling and process interaction approach to discrete-event simu- tion. The book depends on the basic modeling concepts and is more specialized than my previous book: Practical Process Simulation with Object-Oriented Techniques and C++, published by Artech House, Boston 1999. For a more detailed description see the Web location: http://science.kennesaw.edu/~jgarrido/mybook,html. Most other books on performance modeling use only analytical approaches, and very few apply these concepts to the study of operating systems. Thus, the unique feature of the book is that it concentrates on design aspects of operating systems using practical simulation techniques. In addition, the book illustrates the dynamic behavior of different aspects of operating systems using the various simulation models, with a general hands-on approach.

Introduction to Computational Modeling Using C and Open-Source Tools presents the fundamental principles of computational models from a computer science perspective. It explains how to implement these models using the C programming language. The software tools used in the book include the Gnu Scientific Library (GSL), which is a free software library of C functions, and the versatile, open-source GnuPlot for visualizing the data. All source files, shell scripts, and additional notes are located at ksuweb.kennesaw.edu/~jgarrido/comp_models.The book first presents an overview of problem solving and the introductory concepts, principles, and development of computational models before covering the programming principles of the C programming language. The author then applies programming principles and basic numerical techniques, such as polynomial evaluation, regression, and other numerical methods, to implement computational models. He also discusses more advanced concepts needed for modeling dynamical systems and explains how to generate numerical solutions. The book concludes with the modeling of linear optimization problems.Emphasizing analytical skill development and problem solving, this book helps you understand how to reason about and conceptualize the problems, generate mathematical formulations, and computationally visualize and solve the problems. It provides you with the foundation to understand more advanced scientific computing, including parallel computing using MPI, grid computing, and other techniques in high-performance computing.

Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing, such as the Numpy and Scipy modules. The Python source code and data files are available on the author’s website.The book’s five sections present: An overview of problem solving and simple Python programs, introducing the basic models and techniques for designing and implementing problem solutions, independent of software and hardware toolsProgramming principles with the Python programming language, covering basic programming concepts, data definitions, programming structures with flowcharts and pseudo-code, solving problems, and algorithmsPython lists, arrays, basic data structures, object orientation, linked lists, recursion, and running programs under LinuxImplementation of computational models with Python using Numpy, with examples and case studies The modeling of linear optimization problems, from problem formulation to implementation of computational modelsThis book introduces the principles of computational modeling as well as the approaches of multi- and interdisciplinary computing to beginners in the field. It provides the foundation for more advanced studies in scientific computing, including parallel computing using MPI, grid computing, and other methods and techniques used in high-performance computing.

Introduction to Computational Modeling Using C and Open-Source Tools presents the fundamental principles of computational models from a computer science perspective. It explains how to implement these models using the C programming language. The software tools used in the book include the Gnu Scientific Library (GSL), which is a free software libra

Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing, such as the Numpy and Scipy m

Object Oriented Simulation will qualify as a valuable resource to students and accomplished professionals and researchers alike, as it provides an extensive, yet comprehensible introduction to the basic principles of object-oriented modeling, design and implementation of simulation models.Key features include an introduction to modern commercial graphical simulation and animation software, accessible breakdown of OOSimL language constructs through various programming principles, and extensive tutorial materials ideal for undergraduate classroom use.

Object Oriented Simulation will qualify as a valuable resource to students and accomplished professionals and researchers alike, as it provides an extensive, yet comprehensible introduction to the basic principles of object-oriented modeling, design and implementation of simulation models.Key features include an introduction to modern commercial graphical simulation and animation software, accessible breakdown of OOSimL language constructs through various programming principles, and extensive tutorial materials ideal for undergraduate classroom use.

This revised and updated Second Edition presents a practical introduction to operating systems and illustrates these principles through a hands-on approach using accompanying simulation models developed in Java and C++. This text is appropriate for upper-level undergraduate courses in computer science. Case studies throughout the text feature the implementation of Java and C++ simulation models, giving students a thorough look at both the theoretical and the practical concepts discussed in modern OS courses. This pedagogical approach is designed to present a clearer, more practical look at OS concepts, techniques, and methods without sacrificing the theoretical rigor that is necessary at this level. It is an ideal choice for those interested in gaining comprehensive, hands-on experience using the modern techniques and methods necessary for working with these complex systems. Every new printed copy is accompanied with a CD-ROM containing simulations (eBook version does not include CD-ROM).New material added to the Second Edition:- Chapter 11 (Security) has been revised to include the most up-to-date information- Chapter 12 (Firewalls and Network Security) has been updated to include material on middleware that allows applications on separate machines to communicate (e.g. RMI, COM+, and Object Broker)- Includes a new chapter dedicated to Virtual Machines- Provides introductions to various types of scams- Updated to include information on Windows 7 and Mac OS X throughout the text- Contains new material on basic hardware architecture that operating systems depend on- Includes new material on handling multi-core CPUsInstructor Resources:-Answers to the end of chapter questions-PowerPoint Lecture Outlines

Researches and developers of simulation models state that the Java program­ ming language presents a unique and significant opportunity for important changes in the way we develop simulation models today. The most important characteristics of the Java language that are advantageous for simulation are its multi-threading capabilities, its facilities for executing programs across the Web, and its graphics facilities. It is feasible to develop compatible and reusable simulation components that will facilitate the construction of newer and more complex models. This is possible with Java development environments. Another important trend that begun very recently is web-based simulation, i.e., and the execution of simulation models using Internet browser software. This book introduces the application of the Java programming language in discrete-event simulation. In addition, the fundamental concepts and prac­ tical simulation techniques for modeling different types of systems to study their general behavior and their performance are introduced. The approaches applied are the process interaction approach to discrete-event simulation and object-oriented modeling. Java is used as the implementation language and UML as the modeling language. The first offers several advantages compared to C++, the most important being: thread handling, graphical user interfaces (QUI) and Web computing. The second language, UML (Unified Modeling Language) is the standard notation used today for modeling systems as a collection of classes, class relationships, objects, and object behavior.

Researches and developers of simulation models state that the Java program­ ming language presents a unique and significant opportunity for important changes in the way we develop simulation models today. The most important characteristics of the Java language that are advantageous for simulation are its multi-threading capabilities, its facilities for executing programs across the Web, and its graphics facilities. It is feasible to develop compatible and reusable simulation components that will facilitate the construction of newer and more complex models. This is possible with Java development environments. Another important trend that begun very recently is web-based simulation, i.e., and the execution of simulation models using Internet browser software. This book introduces the application of the Java programming language in discrete-event simulation. In addition, the fundamental concepts and prac­ tical simulation techniques for modeling different types of systems to study their general behavior and their performance are introduced. The approaches applied are the process interaction approach to discrete-event simulation and object-oriented modeling. Java is used as the implementation language and UML as the modeling language. The first offers several advantages compared to C++, the most important being: thread handling, graphical user interfaces (QUI) and Web computing. The second language, UML (Unified Modeling Language) is the standard notation used today for modeling systems as a collection of classes, class relationships, objects, and object behavior.

This book introduces the fundamental concepts and practical simulation te- niques for modeling different aspects of operating systems to study their g- eral behavior and their performance. The approaches applied are obje- oriented modeling and process interaction approach to discrete-event simu- tion. The book depends on the basic modeling concepts and is more specialized than my previous book: Practical Process Simulation with Object-Oriented Techniques and C++, published by Artech House, Boston 1999. For a more detailed description see the Web location: http://science.kennesaw.edu/~jgarrido/mybook,html. Most other books on performance modeling use only analytical approaches, and very few apply these concepts to the study of operating systems. Thus, the unique feature of the book is that it concentrates on design aspects of operating systems using practical simulation techniques. In addition, the book illustrates the dynamic behavior of different aspects of operating systems using the various simulation models, with a general hands-on approach.

Introduction to Computational Modeling Using C and Open-Source Tools presents the fundamental principles of computational models from a computer science perspective. It explains how to implement these models using the C programming language. The software tools used in the book include the Gnu Scientific Library (GSL), which is a free software library of C functions, and the versatile, open-source GnuPlot for visualizing the data. All source files, shell scripts, and additional notes are located at ksuweb.kennesaw.edu/~jgarrido/comp_models.The book first presents an overview of problem solving and the introductory concepts, principles, and development of computational models before covering the programming principles of the C programming language. The author then applies programming principles and basic numerical techniques, such as polynomial evaluation, regression, and other numerical methods, to implement computational models. He also discusses more advanced concepts needed for modeling dynamical systems and explains how to generate numerical solutions. The book concludes with the modeling of linear optimization problems.Emphasizing analytical skill development and problem solving, this book helps you understand how to reason about and conceptualize the problems, generate mathematical formulations, and computationally visualize and solve the problems. It provides you with the foundation to understand more advanced scientific computing, including parallel computing using MPI, grid computing, and other techniques in high-performance computing.

Introduction to Computational Modeling Using C and Open-Source Tools presents the fundamental principles of computational models from a computer science perspective. It explains how to implement these models using the C programming language. The software tools used in the book include the Gnu Scientific Library (GSL), which is a free software libra

Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing, such as the Numpy and Scipy modules. The Python source code and data files are available on the author’s website.The book’s five sections present: An overview of problem solving and simple Python programs, introducing the basic models and techniques for designing and implementing problem solutions, independent of software and hardware toolsProgramming principles with the Python programming language, covering basic programming concepts, data definitions, programming structures with flowcharts and pseudo-code, solving problems, and algorithmsPython lists, arrays, basic data structures, object orientation, linked lists, recursion, and running programs under LinuxImplementation of computational models with Python using Numpy, with examples and case studies The modeling of linear optimization problems, from problem formulation to implementation of computational modelsThis book introduces the principles of computational modeling as well as the approaches of multi- and interdisciplinary computing to beginners in the field. It provides the foundation for more advanced studies in scientific computing, including parallel computing using MPI, grid computing, and other methods and techniques used in high-performance computing.