Handbook of Data Intensive Computing

  • Borko Furht
  • Armando Escalante

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Architectures and Systems

    1. Front Matter
      Pages 1-1
    2. Chris A. Mattmann, Daniel J. Crichton, Andrew F. Hart, Cameron Goodale, J. Steven Hughes, Sean Kelly et al.
      Pages 25-57
    3. Anthony M. Middleton, David Alan Bayliss, Gavin Halliday
      Pages 59-107
    4. Abhishek Verma, Shivaram Venkataraman, Matthew Caesar, Roy H. Campbell
      Pages 109-127
  3. Technologies and Techniques

    1. Front Matter
      Pages 155-155
    2. Zhiquan Sui, Shrideep Pallickara
      Pages 157-168
    3. Anthony M. Middleton, David Alan Bayliss
      Pages 189-234
    4. Jonathan Burger, Richard Chapman, Flavio Villanustre
      Pages 235-248
    5. Kerstin Kleese van Dam, Dongsheng Li, Stephen D. Miller, John W. Cobb, Mark L. Green, Catherine L. Ruby
      Pages 249-284
    6. Martin Hahmann, Dirk Habich, Wolfgang Lehner
      Pages 285-321
    7. Wilker Altidor, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
      Pages 349-376
    8. Ling Qin Zhang
      Pages 377-413
    9. Naphtali Rishe, Borko Furht, Malek Adjouadi, Armando Barreto, Debra Davis, Ouri Wolfson et al.
      Pages 415-444
  4. Security

    1. Front Matter
      Pages 445-445
    2. Eduardo B. Fernandez
      Pages 447-466

About this book

Introduction

Data Intensive Computing refers to capturing, managing, analyzing, and understanding data at volumes and rates that push the frontiers of current technologies. The challenge of data intensive computing is to provide the hardware architectures and related software systems and techniques which are capable of transforming ultra-large data into valuable knowledge. Handbook of Data Intensive Computing is written by leading international experts in the field. Experts from academia, research laboratories and private industry address both theory and application. Data intensive computing demands a fundamentally different set of principles than mainstream computing. Data-intensive applications typically are well suited for large-scale parallelism over the data and also require an extremely high degree of fault-tolerance, reliability, and availability. Real-world examples are provided throughout the book.

Handbook of Data Intensive Computing is designed as a reference for practitioners and researchers, including programmers, computer and system infrastructure designers, and developers. This book can also be beneficial for business managers, entrepreneurs, and investors.

Keywords

applications architectures data data intensive computing data storage hardware systems software systems

Editors and affiliations

  • Borko Furht
    • 1
  • Armando Escalante
    • 2
  1. 1.Dept. of Computer Science & EngineeringFlorida Atlantic UniversityBoca RatonUSA
  2. 2.LexisNexisBoca RatonUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-1415-5
  • Copyright Information Springer Science+Business Media, LLC 2011
  • Publisher Name Springer, New York, NY
  • eBook Packages Computer Science
  • Print ISBN 978-1-4614-1414-8
  • Online ISBN 978-1-4614-1415-5
  • About this book