For reasons of clarity, the authors have deliberately chosen examples that apply to machines from all eras, without having to water down the contents of the book. This choice helps to show how techniques, concepts and performances have evolved since the first computers.
The book is divided into five parts. The first four, which are of increasing difficulty, are the core of the book: “Elements of a Basic Architecture”, “Programming Model and Operation”, “Memory Hierarchy”, “Parallelism and Performance Enhancement”. The final part provides hints and solutions to the exercises in the book as well as appendices. The reader may approach each part independently based on their prior knowledge and goals.
Like the popular O'Reilly book, Understanding the Linux Kernel, this book clearly explains the underlying concepts and teaches you how to follow the actual C code that implements it. Although some background in the TCP/IP protocols is helpful, you can learn a great deal from this text about the protocols themselves and their uses. And if you already have a base knowledge of C, you can use the book's code walkthroughs to figure out exactly what this sophisticated part of the Linux kernel is doing.
Part of the difficulty in understanding networks -- and implementing them -- is that the tasks are broken up and performed at many different times by different pieces of code. One of the strengths of this book is to integrate the pieces and reveal the relationships between far-flung functions and data structures. Understanding Linux Network Internals is both a big-picture discussion and a no-nonsense guide to the details of Linux networking. Topics include:Key problems with networkingNetwork interface card (NIC) device driversSystem initializationLayer 2 (link-layer) tasks and implementationLayer 3 (IPv4) tasks and implementationNeighbor infrastructure and protocols (ARP)BridgingRoutingICMP
Author Christian Benvenuti, an operating system designer specializing in networking, explains much more than how Linux code works. He shows the purposes of major networking features and the trade-offs involved in choosing one solution over another. A large number of flowcharts and other diagrams enhance the book's understandability.
This book contributes to our understanding of a number of theories and models. The theoretical contribution of this book is that it analyzes and synthesizes the relevant literature in order to enhance knowledge of IS theories and models from various perspectives. To cater to the information needs of a diverse spectrum of readers, this book is structured into two volumes, with each volume further broken down into two sections.
The first section of Volume 1 presents detailed descriptions of a set of theories centered around the IS lifecycle, including the Success Model, Technology Acceptance Model, User Resistance Theories, and four others. The second section of Volume 1 contains strategic and economic theories, including a Resource-Based View, Theory of Slack Resources, Portfolio Theory, Discrepancy Theory Models, and eleven others.
The first section of Volume 2 concerns socio-psychological theories. These include Personal Construct Theory, Psychological Ownership, Transactive Memory, Language-Action Approach, and nine others. The second section of Volume 2 deals with methodological theories, including Critical Realism, Grounded Theory, Narrative Inquiry, Work System Method, and four others.
Together, these theories provide a rich tapestry of knowledge around the use of theory in IS research. Since most of these theories are from contributing disciplines, they provide a window into the world of external thought leadership.
Information Theory and Best Practices in the IT Industry begins by examining practices of benchmarking productivity and critically appraises them. Next the book identifies different variables which affect productivity and variables that affect quality, developing useful equations that explaining their relationships. Finally these equations and findings are applied to case studies. Utilizing this book, practitioners can decide about what emphasis they should attach to different variables in their own companies, while seeking to optimize productivity and defect density.
Computational Science should enhance the quality of human life, not only solve their problems. Computational Science should help humans to make wise decisions by presenting choices and their possible consequences. Computational Science should help us make sense of observations, understand natural language, plan and reason with extensive background knowledge. Intelligence with wisdom is perhaps an ultimate goal for human-oriented science.
This book is a compilation of some recent research findings in computer application and computational science. This book provides state-of-the-art accounts in Computer Control and Robotics, Computers in Education and Learning Technologies, Computer Networks and Data Communications, Data Mining and Data Engineering, Energy and Power Systems, Intelligent Systems and Autonomous Agents, Internet and Web Systems, Scientific Computing and Modeling, Signal, Image and Multimedia Processing, and Software Engineering.