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  • © 2011

Handbook of Data Intensive Computing

  • Describes and evaluates the current state-of-the-art in new field
  • Presents current systems, and applications from main research labs in this new explosive field
  • Written at a level that business managers, entrepreneurs, and investors will find beneficial
  • Includes supplementary material: sn.pub/extras

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Table of contents (30 chapters)

  1. Front Matter

    Pages i-xviii
  2. Architectures and Systems

    1. Front Matter

      Pages 1-1
  3. ARCHITECTURES AND SYSTEMS

    1. Architecting Data-Intensive Software Systems

      • Chris A. Mattmann, Daniel J. Crichton, Andrew F. Hart, Cameron Goodale, J. Steven Hughes, Sean Kelly et al.
      Pages 25-57
    2. ECL/HPCC: A Unified Approach to Big Data

      • Anthony M. Middleton, David Alan Bayliss, Gavin Halliday
      Pages 59-107
    3. Scalable Storage for Data-Intensive Computing

      • Abhishek Verma, Shivaram Venkataraman, Matthew Caesar, Roy H. Campbell
      Pages 109-127
  4. Technologies and Techniques

    1. Front Matter

      Pages 155-155
  5. TECHNOLOGIES AND TECHNIQUES

    1. A Survey of Load Balancing Techniques for Data Intensive Computing

      • Zhiquan Sui, Shrideep Pallickara
      Pages 157-168
    2. Salt: Scalable Automated Linking Technology for Data-Intensive Computing

      • Anthony M. Middleton, David Alan Bayliss
      Pages 189-234
    3. Parallel Processing, Multiprocessors and Virtualization in Data-Intensive Computing

      • Jonathan Burger, Richard Chapman, Flavio Villanustre
      Pages 235-248
    4. Challenges in Data Intensive Analysis at Scientific Experimental User Facilities

      • Kerstin Kleese van Dam, Dongsheng Li, Stephen D. Miller, John W. Cobb, Mark L. Green, Catherine L. Ruby
      Pages 249-284
    5. Large-Scale Data Analytics Using Ensemble Clustering

      • Martin Hahmann, Dirk Habich, Wolfgang Lehner
      Pages 285-321
    6. Ensemble Feature Ranking Methods for Data Intensive Computing Applications

      • Wilker Altidor, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
      Pages 349-376
    7. Record Linkage Methodology and Applications

      • Ling Qin Zhang
      Pages 377-413
    8. Semantic Wrapper: Concise Semantic Querying of Legacy Relational Databases

      • Naphtali Rishe, Borko Furht, Malek Adjouadi, Armando Barreto, Debra Davis, Ouri Wolfson et al.
      Pages 415-444
  6. Security

    1. Front Matter

      Pages 445-445
  7. SECURITY

    1. Security in Data Intensive Computing Systems

      • Eduardo B. Fernandez
      Pages 447-466

About this book

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 referencefor practitioners and researchers, including programmers, computer and system infrastructure designers, and developers. This book can also be beneficial for business managers, entrepreneurs, and investors. 

Reviews

From the reviews:

“The material is written by experts from nearly 40 institutions, including academia, industry, and government; they are mostly from the US, but also from Europe, Asia, and Australia. … The editors make readers aware of the scale of data generated from a variety of sources, which require immediate comprehensive analyses. … The value of this book might be in collecting papers that focused on the issues of big data, so interested parties can have a handy overview of related problems and prospective solutions.” (Janusz Zalewski, ACM Computing Reviews, September, 2012)

 

Editors and Affiliations

  • Dept. of Computer Science & Engineering, Florida Atlantic University, Boca Raton, USA

    Borko Furht

  • LexisNexis, Boca Raton, USA

    Armando Escalante

About the editors

 

Bibliographic Information

Buy it now

Buying options

eBook USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access