Distributed and Cloud Computing

Distributed and Cloud Computing

Author: Kai Hwang

Publisher: Morgan Kaufmann

Published: 2013-12-18

Total Pages: 671

ISBN-13: 0128002042

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Distributed and Cloud Computing: From Parallel Processing to the Internet of Things offers complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing. It is the first modern, up-to-date distributed systems textbook; it explains how to create high-performance, scalable, reliable systems, exposing the design principles, architecture, and innovative applications of parallel, distributed, and cloud computing systems. Topics covered by this book include: facilitating management, debugging, migration, and disaster recovery through virtualization; clustered systems for research or ecommerce applications; designing systems as web services; and social networking systems using peer-to-peer computing. The principles of cloud computing are discussed using examples from open-source and commercial applications, along with case studies from the leading distributed computing vendors such as Amazon, Microsoft, and Google. Each chapter includes exercises and further reading, with lecture slides and more available online. This book will be ideal for students taking a distributed systems or distributed computing class, as well as for professional system designers and engineers looking for a reference to the latest distributed technologies including cloud, P2P and grid computing. - Complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing - Includes case studies from the leading distributed computing vendors: Amazon, Microsoft, Google, and more - Explains how to use virtualization to facilitate management, debugging, migration, and disaster recovery - Designed for undergraduate or graduate students taking a distributed systems course—each chapter includes exercises and further reading, with lecture slides and more available online


Science Gateways for Distributed Computing Infrastructures

Science Gateways for Distributed Computing Infrastructures

Author: Péter Kacsuk

Publisher: Springer

Published: 2014-10-28

Total Pages: 308

ISBN-13: 3319112686

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The book describes the science gateway building technology developed in the SCI-BUS European project and its adoption and customization method, by which user communities, such as biologists, chemists, and astrophysicists, can build customized, domain-specific science gateways. Many aspects of the core technology are explained in detail, including its workflow capability, job submission mechanism to various grids and clouds, and its data transfer mechanisms among several distributed infrastructures. The book will be useful for scientific researchers and IT professionals engaged in the development of science gateways.


Designing a New Class of Distributed Systems

Designing a New Class of Distributed Systems

Author: Rao Mikkilineni

Publisher: Springer Science & Business Media

Published: 2011-11-02

Total Pages: 74

ISBN-13: 1461419247

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Designing a New Class of Distributed Systems closely examines the Distributed Intelligent Managed Element (DIME) Computing Model, a new model for distributed systems, and provides a guide to implementing Distributed Managed Workflows with High Reliability, Availability, Performance and Security. The book also explores the viability of self-optimizing, self-monitoring autonomous DIME-based computing systems. Designing a New Class of Distributed Systems is designed for practitioners as a reference guide for innovative distributed systems design. Researchers working in a related field will also find this book valuable.


Enabling Technologies and Architectures for Next-Generation Networking Capabilities

Enabling Technologies and Architectures for Next-Generation Networking Capabilities

Author: Elkhodr, Mahmoud

Publisher: IGI Global

Published: 2018-10-19

Total Pages: 399

ISBN-13: 1522560246

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With the rise of mobile and wireless technologies, more sustainable networks are necessary to support communication. These next-generation networks can now be utilized to extend the growing era of the Internet of Things. Enabling Technologies and Architectures for Next-Generation Networking Capabilities is an essential reference source that explores the latest research and trends in large-scale 5G technologies deployment, software-defined networking, and other emerging network technologies. Featuring research on topics such as data management, heterogeneous networks, and spectrum sensing, this book is ideally designed for computer engineers, technology developers, network administrators and researchers, professionals, and graduate-level students seeking coverage on current and future network technologies.


Data Driven e-Science

Data Driven e-Science

Author: Simon C. Lin

Publisher: Springer Science & Business Media

Published: 2011-02-04

Total Pages: 526

ISBN-13: 1441980148

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ISGC 2010, The International Symposium on Grid Computing was held at Academia Sinica, Taipei, Taiwan, March, 2010. The 2010 symposium brought together prestigious scientists and engineers worldwide to exchange ideas, present challenges/solutions and to discuss new topics in the field of Grid Computing. Data Driven e-Science: Use Cases and Successful Applications of Distributed Computing Infrastructures (ISGC 2010), an edited volume, introduces the latest achievements in grid technology for Biomedicine Life Sciences, Middleware, Security, Networking, Digital Library, Cloud Computing and more. This book provides Grid developers and end users with invaluable information for developing grid technology and applications. The last section of this book presents future development in the field of Grid Computing. This book is designed for a professional audience composed of grid users, developers and researchers working in the field of grid computing. Advanced-level students focused on computer science and engineering will also find this book valuable as a reference or secondary text book.


Information Storage and Management

Information Storage and Management

Author: EMC Education Services

Publisher: John Wiley & Sons

Published: 2012-04-30

Total Pages: 528

ISBN-13: 1118236963

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The new edition of a bestseller, now revised and update throughout! This new edition of the unparalleled bestseller serves as a full training course all in one and as the world's largest data storage company, EMC is the ideal author for such a critical resource. They cover the components of a storage system and the different storage system models while also offering essential new material that explores the advances in existing technologies and the emergence of the "Cloud" as well as updates and vital information on new technologies. Features a separate section on emerging area of cloud computing Covers new technologies such as: data de-duplication, unified storage, continuous data protection technology, virtual provisioning, FCoE, flash drives, storage tiering, big data, and more Details storage models such as Network Attached Storage (NAS), Storage Area Network (SAN), Object Based Storage along with virtualization at various infrastructure components Explores Business Continuity and Security in physical and virtualized environment Includes an enhanced Appendix for additional information This authoritative guide is essential for getting up to speed on the newest advances in information storage and management.


Distributed Computing for Emerging Smart Networks

Distributed Computing for Emerging Smart Networks

Author: Imen Jemili

Publisher: Springer Nature

Published: 2022-04-05

Total Pages: 137

ISBN-13: 3030990044

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This book constitutes the refereed proceedings of the Third International Workshop on Distributed Computing for Emerging Smart Networks, DiCES-N 2022, held in Bizerte, Tunisia, in February 2022. Due to the COVID-19 pandemic the conference was held online. The 5 full papers included in this volume were carefully reviewed and selected from 14 submissions. The volume also presents one invited paper. The papers are organized in topical sections on ​emerging networks and communications; cyber security of connected objects.


Frontiers in Massive Data Analysis

Frontiers in Massive Data Analysis

Author: National Research Council

Publisher: National Academies Press

Published: 2013-09-03

Total Pages: 191

ISBN-13: 0309287812

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Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.