Networking and Parallel/Distributed Computing 2012

Focusing on grid computing and asynchronism, Parallel Iterative Algorithms explores the theoretical and practical aspects of parallel numerical algorithms. Each chapter contains a theoretical discussi

From the Internet's infrastructure to operating systems like GNU/Linux, the open source movement comprises some of the greatest accomplishments in computing over the past quarter century. Its story embraces technological advances, unprecedented global collaboration, and remarkable tools for facilitating distributed development. The evolution of the Internet enabled an enormous expansion of open development, allowing developers to exchange information and ideas without regard to constraints of space, time, or national boundary. The movement has had widespread impact on education and government, as well as historic cultural and commercial repercussions. Part I discusses key open source applications, platforms, and technologies used in open development. Part II explores social issues ranging from demographics and psychology to legal and economic matters. Part III discusses the Free Software Foundation, open source in the public sector (government and education), and future prospects.

The eagerly awaited Pattern-Oriented Software Architecture (POSA) Volume 4 is about a pattern language for distributed computing. The authors will guide you through the best practices and introduce y

This book takes a holistic view on mobile and distributed computing systems. It presents innovative solutions at all system layers. These range from hardware over vertical and horizontal infrastructur

Most applications in distributed computing center around a set of common subproblems. Distributed Systems: An Algorithmic Approach presents the algorithmic issues and necessary background theory that

In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of parallelism. The authors begin by giving the reader a deeper understanding of the issues through a general examination of timing, data dependencies, and communication. These ideas are implemented with respect to shared memory, parallel and vector processing, and distributed memory cluster computing. Threads, OpenMP, and MPI are covered, along with code examples in Fortran, C, and Java. The principles of parallel computation are applied throughout as the authors cover traditional topics in a first course in scientific computing. Building on the fundamentals of floating point representation and numerical error, a thorough treatment of numerical linear algebra and eigenvector/eigenvalue problems is provided. By studying how these algorithms parallelize, the reader is able to explore parallelism inherent in other computations, such as Monte Carlo

This book focuses on the aspects related to the parallelization of evolutionary computations, such as parallel genetic operators, parallel fitness evaluation, distributed genetic algorithms, and paral

JavaTech is a practical introduction to the Java programming language with an emphasis on the features that benefit technical computing. After presenting the basics of object-oriented programming in Java, it examines introductory topics such as graphical interfaces and thread processes. It goes on to review network programming and develops Web client-server examples for tasks such as monitoring remote devices. The focus then shifts to distributed computing with RMI. Finally, it examines how Java programs can access the local platform and interact with hardware. Topics include combining native code with Java, communication via serial lines, and programming embedded processors. An extensive web site supports the book with additional instructional materials. JavaTech demonstrates the ease with which Java can be used to create powerful network applications and distributed computing applications. It will be used as a textbook for programming courses, and by researchers who need to learn Jav

Discover grid computing-how to successfully build, implement, and manage widely distributed computing architecture With technology budgets under increasing scrutiny and system architecture becoming m

Master the numerical simulation process required to design, test and support mobile and parallel computing systems. An accompanying ftp site contains all the Visual C++ based programs discussed in the

This self-contained book reviews and describes the key concepts, principles and applications of modern distributed computing systems and architectures. Essential for anyone seeking a solid grounding

A lucid and up-to-date introduction to the fundamentals of distributed computing systemsAs distributed systems become increasingly available, the need for a fundamental discussion of the subject has g

* Ubiquitous computing refers to computers embedded in everyday devices communicating with each other over ad-hoc wireless networks* Focuses on two very hot topics: ad-hoc wireless networking and secu

Originally published in 2002, this book presents techniques in the application of formal methods to object-based distributed systems. A major theme of the book is how to formally handle the requirements arising from OO distributed systems, such as dynamic reconfiguration, encapsulation, subtyping, inheritance, and real-time aspects. These may be supported either by enhancing existing notations, such as UML, LOTOS, SDL and Z, or by defining fresh notations, such as Actors, Pi-calculus and Ambients. The major specification notations and modelling techniques are introduced and compared by leading researchers. The book also includes a description of approaches to the specification of non-functional requirements, and a discussion of security issues. Researchers and practitioners in software design, object-oriented computing, distributed systems, and telecommunications systems will gain an appreciation of the relationships between the major areas of concerns and learn how the use of object-o

This book, first published in 2000, explores the exciting field of complexity. It features in-depth coverage of important theoretical areas, including fractals, chaos, non-linear dynamics, artificial life and self-organization. It also provides overviews of complexity in several applied areas, including parallel computation, control systems, neural systems and ecosystems. Some of the properties that best characterize complex systems, including algorithmic richness, non-linearity and abundant interactions between components are examined. In this way the book draws out themes, especially the ideas of connectivity and natural computation, that reveal deep, underlying similarities between phenomena that have formerly been treated as completely distinct. The idea of natural computation is particularly rich in fresh approaches applicable to both biology and computing. Analogies such as the DNA code as life's underlying program, or organisms as automata, are very compelling. Conversely, biolo

Concurrent Programming in ML focuses on the practical use of concurrency to implement naturally concurrent applications. In addition to a tutorial introduction to programming in Concurrent ML (CML), the book presents three extended examples using CML for practical systems programming: a parallel software build system, a simple concurrent window manager, and an implementation of distributed tuple spaces. CML, which is included as part of the SML of New Jersey (SML/NJ) distribution, combines the best features of concurrent programming and functional programming. This book also illustrates advanced SML programming techniques, and includes a chapter on the implementation of concurrency using features provided by the SML/NJ system. It will be of interest to programmers, students, and professional researchers working in computer language development.

Distributed Computing is rapidly becoming the principal computing paradigm in diverse areas of computing, communication, and control. Processor clusters, local and wide area networks, and the informat

Complex fluid flows are encountered widely in nature, in living beings and in engineering practice. These flows often involve both geometric and dynamic complexity and present problems that are difficult to analyse because of their wide range of length and time scales, as well as their geometric configuration. This book describes some computational techniques and modelling strategies for analysing and predicting complex transport phenomena. It summarizes advances in the context of a pressure-based algorithm. Among methods discussed are discretization schemes for treating convection and pressure, parallel computing, multigrid methods, and composite, multiblock techniques. With respect to physical modelling, the book addresses issues of turbulence closure and multiscale, multiphase transport from an engineering viewpoint. Both fundamental and practical issues are considered, along with the relative merits of competing approaches. Numerous examples are given throughout the text. Mechanica

This book sets out the principles of parallel computing in a way which will be useful to student and potential user alike. It includes coverage of both conventional and neural computers. The content of the book is arranged hierarchically. It explains why, where and how parallel computing is used; the fundamental paradigms employed in the field; how systems are programmed or trained; technical aspects including connectivity and processing element complexity; and how system performance is estimated (and why doing so is difficult). The penultimate chapter of the book comprises a set of case studies of archetypal parallel computers, each study written by an individual closely connected with the system in question. The final chapter correlates the various aspects of parallel computing into a taxonomy of systems.

In this 1991 book, Hilbers discusses the general case of how to use processors simultaneously in order to solve a single problem rather than any specific application, and develops a theory independent of particular architectures. He starts by introducing distributed computing with graph theory, and considers processor networks and their price/performance ratios. He goes on to look at obtaining homogeneous distributions of work over networks and considers examples. Finally he discusses message routing within a processor network. This is intended to be a fundamental treatment of the relevant subjects and is aimed at computer scientists and graduate students in computer science who have experience with parallel processing: it will also be useful to others interested in processor networks.

This book presents the proceedings of the Distributed Ada '89 Symposium held at the University of Southampton in December. The objective of the symposium was to provide a platform for developers and users with experience in the areas of distributed and parallel environments to reveal the advantages and difficulties encountered. The impact of Ada-9X and other enhancements to the language were also explored.

This book presents task-scheduling techniques for emerging complex parallel architectures including heterogeneous multi-core architectures, warehouse-scale datacenters, and distributed big data proces

This book presents a collection of contributions addressing recent advances and research in synergistic combinations of topics in the joint fields of intelligent computing and distributed computing. I

This book discusses advanced topics such as R core programing, object oriented R programing, parallel computing with R, and spatial data types. The author leads readers to merge mature and effective m

This book provides a systematic, foundational introduction to automatic alignment of parallel texts, a family of essential corpus analysis techniques for computing and learning the mappings between co

With contributions from prominent researchers, this is a comprehensive review of state-of-the-art architectures, protocols, technologies and applications in pervasive computing and wireless networking

Developments in parallel computing in recent years have made it possible to build multi-processor architectures that enable efficiency and speed in today's computing environment. Parallel Algorithms a

"Vector Models for Data-Parallel Computing "describes a model of parallelism that extends and formalizes the Data-Parallel model on which the Connection Machine and other supercomputers are based. It

McClelland and Rumelhart's "Parallel Distributed Processing "was the first book to present a definitive account of the newly revived connectionist/neural net paradigm for artificial intelligence and c