Distributed and Cloud Computing

Distributed and Cloud Computing

From Parallel Processing to the Internet of Things

1st Edition - October 17, 2011

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  • Authors: Kai Hwang, Jack Dongarra, Geoffrey Fox
  • Paperback ISBN: 9780123858801
  • eBook ISBN: 9780128002049

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Description

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.

Key Features

  • 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

Readership

Students taking a distributed systems or distributed computing class; also professional system designers and engineers looking for a reference to the latest distributed technologies including cloud, P2P and grid computing.

Table of Contents

  • Dedication

    Preface

    About the Book

    A Glance at the Contents

    Key Features

    Readership and Suggestions to Instructors/Students

    Invited Contributions

    Permissions and Acknowledgements

    About the Authors

    Foreword

    Part 1: Systems Modeling, Clustering, and Virtualization

    Introduction

    Chapter 1: Distributed System Models and Enabling Technologies

    Chapter 2: Computer Clusters for Scalable Parallel Computing

    Chapter 3: Virtual Machines and Virtualization of Clusters and Data Centers

    Chapter 1. Distributed System Models and Enabling Technologies

    Summary

    1.1 Scalable Computing Over the Internet

    1.2 Technologies for Network-Based Systems

    1.3 System Models for Distributed and Cloud Computing

    1.4 Software Environments for Distributed Systems and Clouds

    1.5 Performance, Security, and Energy Efficiency

    1.6 Bibliographic Notes and Homework Problems

    Acknowledgments

    References

    Homework Problems

    Chapter 2. Computer Clusters for Scalable Parallel Computing

    Summary

    2.1 Clustering for Massive Parallelism

    2.2 Computer Clusters and MPP Architectures

    2.3 Design Principles of Computer Clusters

    2.4 Cluster Job and Resource Management

    2.5 Case Studies of Top Supercomputer Systems

    2.6 Bibliographic Notes and Homework Problems

    Acknowledgments

    References

    Homework Problems

    Chapter 3. Virtual Machines and Virtualization of Clusters and Data Centers

    Summary

    3.1 Implementation Levels of Virtualization

    3.2 Virtualization Structures/Tools and Mechanisms

    3.3 Virtualization of CPU, Memory, and I/O Devices

    3.4 Virtual Clusters and Resource Management

    3.5 Virtualization for Data-Center Automation

    3.6 Bibliographic Notes and Homework Problems

    Acknowledgments

    References

    Homework Problems

    Part 2: Computing Clouds, Service-Oriented Architecture, and Programming

    Introduction

    Chapter 4: Cloud Platform Architecture over Virtualized Data Centers

    Chapter 5: Service-Oriented Architectures for Distributed Computing

    Chapter 6: Cloud Programming and Software Environments

    Chapter 4. Cloud Platform Architecture over Virtualized Data Centers

    Summary

    4.1 Cloud Computing and Service Models

    4.2 Data-Center Design and Interconnection Networks

    4.3 Architectural Design of Compute and Storage Clouds

    4.4 Public Cloud Platforms: GAE, AWS, and Azure

    4.5 Inter-cloud Resource Management

    4.6 Cloud Security and Trust Management

    4.7 Bibliographic Notes and Homework Problems

    Acknowledgements

    References

    Homework Problems

    Chapter 5. Service-Oriented Architectures for Distributed Computing

    Summary

    5.1 Services and Service-Oriented Architecture

    5.2 Message-Oriented Middleware

    5.3 Portals and Science Gateways

    5.4 Discovery, Registries, Metadata, and Databases

    5.5 Workflow in Service-Oriented Architectures

    5.6 Bibliographic Notes and Homework Problems

    Acknowledgements

    References

    Homework Problems

    Chapter 6. Cloud Programming and Software Environments

    Summary

    6.1 Features of Cloud and Grid Platforms

    6.2 Parallel and Distributed Programming Paradigms

    6.3 Programming Support of Google App Engine

    6.4 Programming on Amazon AWS and Microsoft Azure

    6.5 Emerging Cloud Software Environments

    6.6 Bibliographic Notes and Homework Problems

    Acknowledgement

    References

    Homework Problems

    Part 3: Grids, P2P, and the Future Internet

    Introduction

    Chapter 7: Grid Computing Systems and Resource Management

    Chapter 8: Peer-to-Peer Computing and Overlay Networks

    Chapter 9: Ubiquitous Clouds and the Internet of Things

    Chapter 7. Grid Computing Systems and Resource Management

    Summary

    7.1 Grid Architecture and Service Modeling

    7.2 Grid Projects and Grid Systems Built

    7.3 Grid Resource Management and Brokering

    7.4 Software and Middleware for Grid Computing

    7.5 Grid Application Trends and Security Measures

    7.6 Bibliographic Notes and Homework Problems

    Acknowledgments

    References

    Homework Problems

    Chapter 8. Peer-to-Peer Computing and Overlay Networks

    Summary

    8.1 Peer-to-Peer Computing Systems

    8.2 P2P Overlay Networks and Properties

    8.3 Routing, Proximity, and Fault Tolerance

    8.4 Trust, Reputation, and Security Management

    8.5 P2P File Sharing and Copyright Protection

    8.6 Bibliographic Notes and Homework Problems

    Acknowledgements

    References

    Homework Problems

    Chapter 9. Ubiquitous Clouds and the Internet of Things

    Summary

    9.1 Cloud Trends in Supporting Ubiquitous Computing

    9.2 Performance of Distributed Systems and the Cloud

    9.3 Enabling Technologies for the Internet of Things

    9.4 Innovative Applications of the Internet of Things

    9.5 Online Social and Professional Networking

    9.6 Bibliographic Notes and Homework Problems

    Acknowledgements

    References

    Homework Problems

    Index

Product details

  • No. of pages: 672
  • Language: English
  • Copyright: © Morgan Kaufmann 2011
  • Published: October 17, 2011
  • Imprint: Morgan Kaufmann
  • Paperback ISBN: 9780123858801
  • eBook ISBN: 9780128002049

About the Authors

Kai Hwang

Kai Hwang is a Professor of Computer Engineering, University of Southern California and an IV-endowed visiting Chair Professor, Tsinghua University, China. He earned the Ph.D. in EECS from University of California at Berkeley. An IEEE Life Fellow, He has published extensively in computer architecture, digital arithmetic, parallel processing, distributed systems, Internet security, and cloud computing. He has founded the Journal of Parallel and Distributed Computing and delivered three dozens of keynote addresses in major IEEE/ACM Conferences. He received the 2004 Outstanding Achievement Award from China Computer Federation and the IEEE 2011 IPDPS Founders' Award for his pioneering contributions in the field of parallel processing.

Affiliations and Expertise

University of Southern California, USA

Jack Dongarra

Jack Dongarra is a University Distinguished Professor of Electrical Engineering and Computer Science, University of Tennessee, a Distinguished Research Staff, Oak Ridge National Laboratory and a Turning Fellow at the University of Manchester. An ACM/IEEE/ SIAM/AAAS Fellow, Dongarra pioneered the areas of supercomputer benchmarks, numerical analysis, linear algebra solvers, and high-performance computing and published extensively in these areas. He leads the Linpack benchmark evaluation of the Top-500 fastest computers over the years. Based on his high contributions in the supercomputing and high-performance areas, he was elected as a Member of the National Academy of Engineering in the USA.

Affiliations and Expertise

University of Tennessee, USA

Geoffrey Fox

Geoffrey Fox is a Distinguished Professor of Informatics, Computing and Physics and Associate Dean of Graduate studies and Research in the School of Informatics and Computing, Indiana University. He has taught and led many research groups at Caltech and Syracuse University, previously. He received his Ph.D. from Cambridge University, U.K. Fox is well known for his comprehensive work and extensive publications in parallel architecture, distributed programming, grid computing, web services, and Internet applications. His book on Grid Computing (coauthored with F. Berman and Tony Hey) is widely used by the research community. He has produced over 60 Ph.D. students in physics, computer science and engineering over the years.

Affiliations and Expertise

Indiana University, USA

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