Introduction to Distributed Computer Systems, Czaja
Автор: Cormen, Thomas H., E Название: Introduction to algorithms 3 ed. ISBN: 0262033844 ISBN-13(EAN): 9780262033848 Издательство: MIT Press Рейтинг: Цена: 183920.00 T Наличие на складе: Нет в наличии. Описание: A new edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-base flow.
Автор: Wooldridge, Michael Название: Introduction to multiagent systems ISBN: 0470519460 ISBN-13(EAN): 9780470519462 Издательство: Wiley Рейтинг: Цена: 60140.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The eagerly anticipated updated resource on one of the most important areas of research and development: multi-agent systems Multi-agent systems allow many intelligent agents to interact with each other, and this field of study has advanced at a rapid pace since the publication of the first edition of this book, which was nearly a decade ago.
Автор: Bradley Efron and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 60190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Автор: Burns Brendan Название: Designing Distributed Systems: Patterns and Paradigms for Scalable, Reliable Services ISBN: 1491983647 ISBN-13(EAN): 9781491983645 Издательство: Wiley Рейтинг: Цена: 42230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This report explores the concept of a digital business platform as a way of empowering individual business sectors to act on data in real time.
Автор: Karine Altisen, Stephane Devismes, Swan Dubois, Franck Petit Название: Introduction to Distributed Self-Stabilizing Algorithms ISBN: 1681735369 ISBN-13(EAN): 9781681735368 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 72070.00 T Наличие на складе: Нет в наличии. Описание: This book aims at being a comprehensive and pedagogical introduction to the concept of self-stabilization , introduced by Edsger Wybe Dijkstra in 1973. Self-stabilization characterizes the ability of a distributed algorithm to converge within finite time to a configuration from which its behavior is correct (i.e., satisfies a given specification), regardless the arbitrary initial configuration of the system. This arbitrary initial configuration may be the result of the occurrence of a finite number of transient faults. Hence, self-stabilization is actually considered as a versatile non-masking fault tolerance approach, since it recovers from the effect of any finite number of such faults in a unified manner. Another major interest of such an automatic recovery method comes from the difficulty of resetting malfunctioning devices in a large-scale (and so, geographically spread) distributed system (the Internet, Pair-to-Pair networks, and Delay Tolerant Networks are examples of such distributed systems). Furthermore, self-stabilization is usually recognized as a lightweight property to achieve fault tolerance as compared to other classical fault tolerance approaches. Indeed, the overhead, both in terms of time and space, of state-of-the-art self-stabilizing algorithms is commonly small. This makes self-stabilization very attractive for distributed systems equipped of processes with low computational and memory capabilities, such as wireless sensor networks. After more than 40 years of existence, self-stabilization is now sufficiently established as an important field of research in theoretical distributed computing to justify its teaching in advanced research-oriented graduate courses. This book is an initiation course, which consists of the formal definition of self-stabilization and its related concepts, followed by a deep review and study of classical (simple) algorithms, commonly used proof schemes and design patterns, as well as premium results issued from the self-stabilizing community. As often happens in the self-stabilizing area, in this book we focus on the proof of correctness and the analytical complexity of the studied distributed self-stabilizing algorithms. Finally, we underline that most of the algorithms studied in this book are actually dedicated to the high-level atomic-state model , which is the most commonly used computational model in the self-stabilizing area. However, in the last chapter, we present general techniques to achieve self-stabilization in the low-level message passing model, as well as example algorithms.
Автор: Eloranta Veli Pekka Название: Designing Distributed Control Systems ISBN: 1118694155 ISBN-13(EAN): 9781118694152 Издательство: Wiley Рейтинг: Цена: 44350.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Designing Distributed Control Systems presents 80 patterns for designing distributed machine control system software architecture (forestry machinery, mining drills, elevators, etc.).
Автор: Miroslav Kubat Название: An Introduction to Machine Learning ISBN: 3319348868 ISBN-13(EAN): 9783319348865 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications.
Автор: Ghosh Sukumar Название: Distributed Systems: An Algorithmic Approach, Second Edition ISBN: 1466552972 ISBN-13(EAN): 9781466552975 Издательство: Taylor&Francis Рейтинг: Цена: 127600.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Distributed Systems: An Algorithmic Approach, Second Edition provides a balanced and straightforward treatment of the underlying theory and practical applications of distributed computing. As in the previous version, the language is kept as unobscured as possible--clarity is given priority over mathematical formalism. This easily digestible text:
Features significant updates that mirror the phenomenal growth of distributed systems
Explores new topics related to peer-to-peer and social networks
Includes fresh exercises, examples, and case studies
Supplying a solid understanding of the key principles of distributed computing and their relationship to real-world applications, Distributed Systems: An Algorithmic Approach, Second Edition makes both an ideal textbook and a handy professional reference.
Название: Advanced distributed measuring systems - exhibits of applications ISBN: 8792329721 ISBN-13(EAN): 9788792329721 Издательство: Taylor&Francis Рейтинг: Цена: 99010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Measuring systems are an essential part of all automated production systems. They can serve to ensure the quality of production, or they can be used to assure the reliability and safety in various areas. The same applies in principle for fields of telecommunication, energy production and distribution, health care, etc. Similarly, no serious scientific research in the field of natural and technical sciences can be performed without objective data about the investigated object, which is usually acquired using measuring system. Demands on the speed and accuracy of measurement increase in all areas in general. These are the grounds for publishing this book.
Advanced Distributed Measuring Systems: Exhibits of Application offers eight up-to-date examples of typical laboratory, industrial, and biomedical applications of advanced measuring and information systems, including virtual instrumentation. The book arose based on the most interesting papers from this area published at IDAACS 2011 conference. However, single chapters include not only system design solution in wider context but also relevant theoretical parts, achieved results, and possible future ways of design and development.
Technical topics discussed in the book include: - embedded applications; - small distributed systems; - automotive distributed system; - distributed monitoring systems based on wireless networks; - synchronization in large DAQ systems; - virtual instrumentation.
Advanced Distributed Measuring Systems: Exhibits of Application is ideal for personnel of firms dealing with control systems, automotive electronics, airspace instrumentation, health care technology, etc. as well as academic staff and postgraduate students in electrical, control, and computer engineering.
Автор: Sai Zhang, Cihan Tepedelenlioglu, Andreas Spanias, Mahesh Banavar Название: Distributed Network Structure Estimation Using Consensus Methods ISBN: 1681732904 ISBN-13(EAN): 9781681732909 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 46200.00 T Наличие на складе: Невозможна поставка. Описание: The area of detection and estimation in a distributed wireless sensor network (WSN) has several applications, including military surveillance, sustainability, health monitoring, and Internet of Things (IoT). Compared with a wired centralized sensor network, a distributed WSN has many advantages including scalability and robustness to sensor node failures. In this book, we address the problem of estimating the structure of distributed WSNs. First, we provide a literature review in: (a) graph theory; (b) network area estimation; and (c) existing consensus algorithms, including average consensus and max consensus. Second, a distributed algorithm for counting the total number of nodes in a wireless sensor network with noisy communication channels is introduced. Then, a distributed network degree distribution estimation (DNDD) algorithm is described. The DNDD algorithm is based on average consensus and in-network empirical mass function estimation. Finally, a fully distributed algorithm for estimating the center and the coverage region of a wireless sensor network is described. The algorithms introduced are appropriate for most connected distributed networks. The performance of the algorithms is analyzed theoretically, and simulations are performed and presented to validate the theoretical results. In this book, we also describe how the introduced algorithms can be used to learn global data information and the global data region.
Автор: Sai Zhang, Cihan Tepedelenlioglu, Andreas Spanias, Mahesh Banavar Название: Distributed Network Structure Estimation Using Consensus Methods ISBN: 1681732920 ISBN-13(EAN): 9781681732923 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 66530.00 T Наличие на складе: Невозможна поставка. Описание: The area of detection and estimation in a distributed wireless sensor network (WSN) has several applications, including military surveillance, sustainability, health monitoring, and Internet of Things (IoT). Compared with a wired centralized sensor network, a distributed WSN has many advantages including scalability and robustness to sensor node failures. In this book, we address the problem of estimating the structure of distributed WSNs. First, we provide a literature review in: (a) graph theory; (b) network area estimation; and (c) existing consensus algorithms, including average consensus and max consensus. Second, a distributed algorithm for counting the total number of nodes in a wireless sensor network with noisy communication channels is introduced. Then, a distributed network degree distribution estimation (DNDD) algorithm is described. The DNDD algorithm is based on average consensus and in-network empirical mass function estimation. Finally, a fully distributed algorithm for estimating the center and the coverage region of a wireless sensor network is described. The algorithms introduced are appropriate for most connected distributed networks. The performance of the algorithms is analyzed theoretically, and simulations are performed and presented to validate the theoretical results. In this book, we also describe how the introduced algorithms can be used to learn global data information and the global data region.
Автор: Gabor Kecskemeti Название: Applying Integration Techniques and Methods in Distributed Systems ISBN: 1522582959 ISBN-13(EAN): 9781522582953 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 239310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Distributed systems intertwine with our everyday lives. The benefits and current shortcomings of the underpinning technologies are experienced by a wide range of people and their smart devices. With the rise of large-scale IoT and similar distributed systems, cloud bursting technologies, and partial outsourcing solutions, private entities are encouraged to increase their efficiency and offer unparalleled availability and reliability to their users. Applying Integration Techniques and Methods in Distributed Systems is a critical scholarly publication that defines the current state of distributed systems, determines further goals, and presents architectures and service frameworks to achieve highly integrated distributed systems and presents solutions to integration and efficient management challenges faced by current and future distributed systems. Highlighting topics such as multimedia, programming languages, and smart environments, this book is ideal for system administrators, integrators, designers, developers, researchers, and academicians.
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