Parallel and Distributed Computing and Networks

This comprehensive treatment of network information theory and its applications provides the first unified coverage of both classical and recent results. With an approach that balances the introduction of new models and new coding techniques, readers are guided through Shannon's point-to-point information theory, single-hop networks, multihop networks, and extensions to distributed computing, secrecy, wireless communication, and networking. Elementary mathematical tools and techniques are used throughout, requiring only basic knowledge of probability, whilst unified proofs of coding theorems are based on a few simple lemmas, making the text accessible to newcomers. Key topics covered include successive cancellation and superposition coding, MIMO wireless communication, network coding, and cooperative relaying. Also covered are feedback and interactive communication, capacity approximations and scaling laws, and asynchronous and random access channels. This book is ideal for use in the

Replication is a topic of interest in the distributed computing, distributed systems, and database communities. Although these communities have traditionally looked at replication from different viewp

This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an active field of research and practice in artificial intelligence, operations research and statistics. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. Yang Xiang extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results. The framework developed in the book allows distributed representation of uncertain knowledge on a large and complex environment embedded in multiple cooperative agents, and effective, exact and distributed probabilistic inference.

This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an active field of research and practice in artificial intelligence, operations research and statistics. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. Yang Xiang extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results. The framework developed in the book allows distributed representation of uncertain knowledge on a large and complex environment embedded in multiple cooperative agents, and effective, exact and distributed probabilistic inference.

This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by real-time performance requirements. Making task-appropriate algorithm and platform choices for large-scale machine learning requires understanding the benefits, trade-offs and constraints of the available options. Solutions presented in the book cover a range of parallelization platforms from FPGAs and GPUs to multi-core systems and commodity clusters, concurrent programming frameworks including CUDA, MPI, MapReduce and DryadLINQ, and learning settings (supervised, unsupervised, semi-supervised and online learning). Extensive coverage of parallelization of boosted trees, SVMs, spectral clustering, belief propagation and other popular learning algo

From its earliest days, the Fortran programming language has been designed with computing efficiency in mind. The latest standard, Fortran 2008, incorporates a host of modern features, including object-orientation, array operations, user-defined types, and provisions for parallel computing. This tutorial guide shows Fortran programmers how to apply these features in twenty-first-century style: modular, concise, object-oriented, and resource-efficient, using multiple processors. It offers practical real-world examples of interfacing to C, memory management, graphics and GUIs, and parallel computing using MPI, OpenMP, and coarrays. The author also analyzes several numerical algorithms and their implementations and illustrates the use of several open source libraries. Full source code for the examples is available on the book's website.

From its earliest days, the Fortran programming language has been designed with computing efficiency in mind. The latest standard, Fortran 2008, incorporates a host of modern features, including object-orientation, array operations, user-defined types, and provisions for parallel computing. This tutorial guide shows Fortran programmers how to apply these features in twenty-first-century style: modular, concise, object-oriented, and resource-efficient, using multiple processors. It offers practical real-world examples of interfacing to C, memory management, graphics and GUIs, and parallel computing using MPI, OpenMP, and coarrays. The author also analyzes several numerical algorithms and their implementations and illustrates the use of several open source libraries. Full source code for the examples is available on the book's website.

Large-scale data analysis ("Big Data") is suddenly of crucial importance to virtually every enterprise. Mobile and social technologies are generating massive datasets, and distributed cloud computing

Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of le

Creating scientific workflow applications is a very challenging task due to the complexity of the distributed computing environments involved, the complex control and data flow requirements of scienti

Driven by the increasing demand for capacity and Quality of Service in wireless cellular networks and motivated by the distributed antenna system, the authors proposed a cooperative communication arch

This book discusses advanced topics?such as?R core programing, object oriented R programing, parallel computing with R, and spatial data types. The author will lead readers to merge mature and effecti

This text identifies, examines, and illustrates fundamental concepts in computer system design that are common across operating systems, networks, database systems, distributed systems, programming la

Process algebra is a widely accepted and much used technique in the specification and verification of parallel and distributed software systems. This book sets the standard for the field. It assembles the relevant results of most process algebras currently in use, and presents them in a unified framework and notation. The authors describe the theory underlying the development, realization and maintenance of software that occurs in parallel or distributed systems. A system can be specified in the syntax provided, and the axioms can be used to verify that a composed system has the required external behaviour. As examples, two protocols are completely specified and verified in the text: the Alternating-Bit Protocol for Data Communication, and Fischer's Protocol of Mutual Exclusion. The book serves as a reference text for researchers and graduate students in computer science, offering a complete overview of the field and referring to further literature where appropriate.

This companion volume to the book Understanding Telecommunications Networks will be of interest to undergraduate and graduate students studying engineering, computing and telecommunications, and for p

This book is about the development of technologies to build smart cities. It is based on a deep experience in the domains of artificial intelligence, distributed and cloud computing as well as sensor

The migration of computing from dedicated appliances to physical environments, thanks to increasingly proliferating microchips and ever-expanding information networks directly implicates and empowers

Scalable Linear Algebra Package (ScaLAPACK) or Scalable LAPACK is a library of linear algebra routines for distributed memory message-passing MIMD computers and networks of workstations supporting par

Medical decision making has evolved in recent years, as more complex problems are being faced and addressed based on increasingly large amounts of data. In parallel, advances in computing have led to

We are now confronted with a new type of uncanny experience, an uncanny evoked by parallel processing, aggregate data, and cloud-computing. The digital uncanny does not erase the uncanny feeling we ex

We are now confronted with a new type of uncanny experience, an uncanny evoked by parallel processing, aggregate data, and cloud-computing. The digital uncanny does not erase the uncanny feeling we ex

This brief focuses on medium access control (MAC) in vehicular ad hoc networks (VANETs), and presents VeMAC, a novel MAC scheme based on distributed time division multiple access (TDMA) for VANETs. Th

2011年漢諾威工業博覽會倡議「工業4.0」概念後，世界經濟論壇（WEF）即具體化解釋概念，定義為「智慧與互聯」的生產系統，意指感知及預測物理世界並與之互動，以便能夠即時支持生產決策。而在各主要科技大國重視「工業4.0」的政策驅動下，也各自發展出不同的架構模型，但卻始終未脫離智慧化、互聯及整合等核心範疇。工業4.0概念更重視分析數據結果以作為生產決策，即透過「物聯網、人工智慧、大數據、雲端運算」等關鍵技術為基礎，建構工業4.0的相關應用，將生產流程從自動化邁向智慧化。工業4.0概念倡議至今十餘年，Siemens等自動化大廠已經成為引領產業發展的指標業者，而IBM、AWS等IT業者也積極的投入智慧製造，發展應用平台或數位工具。智慧製造解決方案可區分為機器運作端（機）、廠務管理端（廠）、營運管理端（鏈）三個環節，再依特性區分為不同的階段性新興應用。本書剖析建構智慧製造的關鍵因素，值得產業解決方案商及建置智慧工廠業者參考。由於涉及異質技術整合應用，數位雙生（Digital Twin）成為智慧製造發展的關鍵挑戰，隨著感測、運算、通訊、軟體技術的革新發展，IT與OT業者在產品服務整合趨勢下，也已經逐步實現並落地於智慧製造場域。近年來國際大廠推動發展智慧製造及數位雙生的技術革新、布局動態與技術未來發展焦點，值得台廠關注以掌握未來的挑戰與契機。邊緣運算（Edge Computing）及新興通訊技術的落地結合，是邁向製造場域關鍵智慧應用的「最後一哩路」。唯有在低延遲、高可靠的邊緣運算與新興通訊框架的驅動下，如「預測性維護、異質設備協作、MR/AR巡檢」等智慧製造應用才可望實現。近年來製造業受到新冠疫情、地緣政治動盪衝擊、及淨零碳排時程迫近等因素影響，對於導入遠距生產、自動化管理的智慧化需求日漸增溫，對供應鏈上下游訊息掌握度的要求也在逐漸提升，而工廠智慧化的關鍵「數據」也漸被重視。各類新型態的數據治理（Data Governance）技術，被應用於不同製造環節的情境與案例，以及數據治理技術發展的最新趨勢分析，都是製造業者面對外部環境變動與挑戰的重要參考資訊。臺灣中小型製造業是經濟發展的重要支柱，提升產業韌性實屬刻不容緩。如何檢視現行可用資源、善用數位科技轉型與提升競爭力，當業者必須面臨「公司資源有限、技術負債尚存、既有組織窠臼、缺乏數位人才」的數位轉型四大挑戰之際，如何提早盤點本身能

This book aims to promote a sample of current theoretical and application oriented intelligent systems research specifically in the field of neural networks computing. It presents examples of experime

Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science.

This book presents an easy-to-read discussion of domain decomposition algorithms, their implementation and analysis. The relationship between domain decomposition and multigrid methods is carefully explained at an elementary level, and discussions of the implementation of domain decomposition methods on massively parallel super computers are also included. All algorithms are fully described and explained, and a mathematical framework for the analysis and complete understanding of the methods is also carefully developed. In addition, numerous numerical examples are included to demonstrate the behaviour of this important class of numerical methods. This book is ideal for graduate students about to embark on a career in computational science. It will also be a valuable resource for all those interested in parallel computing and numerical computational methods.

Following the emergence of quantum computing, the subsequent quantum revolution will be that of interconnecting individual quantum computers at the global level. In the same way that classical computers only realised their full potential with the emergence of the internet, a fully-realised quantum internet is the next stage of evolution for quantum computation. This cutting-edge book examines in detail how the quantum internet would evolve in practise, focusing not only on the technology itself, but also the implications it will have economically and politically, with numerous non-technical sections throughout the text providing broader context to the discussion. The book begins with a description of classical networks before introducing the key concepts behind quantum networks, such as quantum internet protocols, quantum cryptography, and cloud quantum computing. Written in an engaging style and accessible to graduate students in physics, engineering, computer science and mathematics.

An intuitive and accessible text explaining the fundamentals and applications of graph signal processing. Requiring only an elementary understanding of linear algebra, it covers both basic and advanced topics, including node domain processing, graph signal frequency, sampling, and graph signal representations, as well as how to choose a graph. Understand the basic insights behind key concepts and learn how graphs can be associated to a range of specific applications across physical, biological and social networks, distributed sensor networks, image and video processing, and machine learning. With numerous exercises and Matlab examples to help put knowledge into practice, and a solutions manual available online for instructors, this unique text is essential reading for graduate and senior undergraduate students taking courses on graph signal processing, signal processing, information processing, and data analysis, as well as researchers and industry professionals.

Interoperability in IoT for Smart Systems discusses the different facets of interoperability issues among the IoT devices and their solutions, the scalability issues in an IoT network, and provides solutions for plug-n-play of new devices with the existing IoT system. It also addresses the possible usage of interoperable and plug-n-play IoT networks in different systems to make them smarter. Aimed at researchers and graduate students in computer science, computer engineering, computer networks, electronics engineering, this bookExclusively covers interoperability of IoT systems in parallel with their use towards the development of smart systems Discusses the requirements of interoperability in smart IoT systems and their solutions Reviews IoT applications in different smart and intelligent systems Explores dealing with interoperability of heterogeneous participating devices Provides different case studies and open problems related to interoperability in IoT systems

Gain a detailed understanding of the protocols, network architectures and techniques being considered for 5G wireless networks with this authoritative guide to the state of the art. • Get up to speed with key topics such as cloud radio access networks, mobile edge computing, full duplexing, massive MIMO, mmWave, NOMA, Internet of things, M2M communications, D2D communications, mobile data offloading, interference mitigation techniques, radio resource management, visible light communications, and smart data pricing. • Learn from leading researchers in academia and industry about the most recent theoretical developments in the field. • Discover how each potential technology can increase the capacity, spectral efficiency, and energy efficiency of wireless systems. Providing the most comprehensive overview of 5G technologies to date, this is an essential reference for researchers, practicing engineers and graduate students working in wireless communications and networking.

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.

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.

●The learning approach fits the way students are learning today. Instead of a history lesson on the microchip, the focus is on tasks students can accomplish with their computing devices and skills they can apply immediately in the workplace, the classroom, and at home. The content is complemented by hands-on technology, and weekly news feeds to enrich the student learning experience.●All the content is up to date: students stay engaged because the content focuses on the material they want to learn (e.g., how to integrate computing devices into a home network), while teaching the material they need to learn (e.g., how networks work).●The sequence of topics is set up to mirror the typical student learning experience, so that they progress through stages of increasing difficulty.●This progressive approach intentionally introduces topics on a basic level in the earlier chapters and then later expands on those concepts in more detail when students have become more comfortable with them.●The

The support of Java Report by the pioneers of the language has always made it the 'magazine of record' for Java development. From the very beginnings of Java, Java Report was there, examining each new aspect of the language with a clear independent eye. Now, Dwight Deugo, the editor of Java Report, has gathered the most important articles from the first year of the magazine. Written by a who's who of industry experts, Java Gems covers today's most important aspects of Java development. Java Gems' top writers and developers walk you through the topic areas that are essential to today's Java developers, including multitasking, design patterns, class libraries, persistence, distributed computing, and Java vs C++.

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

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

Stochastic resonance has been observed in many forms of systems, and has been hotly debated by scientists for over 30 years. Applications incorporating aspects of stochastic resonance may yet prove revolutionary in fields such as distributed sensor networks, nano-electronics, and biomedical prosthetics. Ideal for researchers in fields ranging from computational neuroscience through to electronic engineering, this book addresses in detail various theoretical aspects of stochastic quantization, in the context of the suprathreshold stochastic resonance effect. Initial chapters review stochastic resonance and outline some of the controversies and debates that have surrounded it. The book then discusses suprathreshold stochastic resonance, and its extension to more general models of stochastic signal quantization. Finally, it considers various constraints and tradeoffs in the performance of stochastic quantizers, before culminating with a chapter in the application of suprathreshold stochas

Stochastic resonance has been observed in many forms of systems, and has been hotly debated by scientists for over 30 years. Applications incorporating aspects of stochastic resonance may yet prove revolutionary in fields such as distributed sensor networks, nano-electronics, and biomedical prosthetics. Ideal for researchers in fields ranging from computational neuroscience through to electronic engineering, this book addresses in detail various theoretical aspects of stochastic quantization, in the context of the suprathreshold stochastic resonance effect. Initial chapters review stochastic resonance and outline some of the controversies and debates that have surrounded it. The book then discusses suprathreshold stochastic resonance, and its extension to more general models of stochastic signal quantization. Finally, it considers various constraints and tradeoffs in the performance of stochastic quantizers, before culminating with a chapter in the application of suprathreshold stochas

The thalamus is a key structure in the mammalian brain, providing a hub for communication within and across distributed forebrain networks. Research in this area has undergone a revolution in the last decade, with findings that suggest an expanded role for the thalamus in sensory processing, motor control, arousal regulation, and cognition. Moving beyond previous studies of anatomy and cell neurochemistry, scientists have expanded into investigations of cognitive function, and harness new methods and theories of neural computation. This book provides a survey of topics at the cutting edge of this field, covering basic anatomy, evolution, development, physiology and computation. It is also the first book to combine these disciplines in one place, highlighting the interdisciplinary nature of thalamus research, and will be an essential resource for students and experts in biology, medicine and computer science.

Distributed applications are difficult to write as programmers need to adhere to specific distributed systems programming conventions and frameworks, which makes distributed systems development comple