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Cloud Computing for Data-Intensive Applications

Overview of attention for book
Cover of 'Cloud Computing for Data-Intensive Applications'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Scalable Deployment of a LIGO Physics Application on Public Clouds: Workflow Engine and Resource Provisioning Techniques
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    Chapter 2 The FutureGrid Testbed for Big Data
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    Chapter 3 Cloud Networking to Support Data Intensive Applications
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    Chapter 4 IaaS Cloud Benchmarking: Approaches, Challenges, and Experience
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    Chapter 5 GPU-Accelerated Cloud Computing for Data-Intensive Applications
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    Chapter 6 Adaptive Workload Partitioning and Allocation for Data Intensive Scientific Applications
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    Chapter 7 DRAW: A New Data-gRouping-AWare Data Placement Scheme for Data Intensive Applications with Interest Locality
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    Chapter 8 Efficient Task-Resource Matchmaking Using Self-adaptive Combinatorial Auction
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    Chapter 9 Federating Advanced Cyberinfrastructures with Autonomic Capabilities
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    Chapter 10 Migrating Scientific Workflow Management Systems from the Grid to the Cloud
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    Chapter 11 Executing Storm Surge Ensembles on PAAS Cloud
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    Chapter 12 Cross-Phase Optimization in MapReduce
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    Chapter 13 Asynchronous Computation Model for Large-Scale Iterative Computations
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    Chapter 14 Big Data Storage and Processing on Azure Clouds: Experiments at Scale and Lessons Learned
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    Chapter 15 Storage and Data Life Cycle Management in Cloud Environments with FRIEDA
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    Chapter 16 Managed File Transfer as a Cloud Service
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    Chapter 17 Supporting a Social Media Observatory with Customizable Index Structures: Architecture and Performance
Overall attention for this book and its chapters
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Title
Cloud Computing for Data-Intensive Applications
Published by
Springer New York, January 2014
DOI 10.1007/978-1-4939-1905-5
ISBNs
978-1-4939-1904-8, 978-1-4939-1905-5
Editors

Li, Xiaolin, Qiu, Judy

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 2 3%
United Kingdom 1 2%
Spain 1 2%
Germany 1 2%
Unknown 53 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 21%
Researcher 9 16%
Student > Master 8 14%
Student > Bachelor 5 9%
Professor 3 5%
Other 11 19%
Unknown 10 17%
Readers by discipline Count As %
Computer Science 34 59%
Engineering 4 7%
Business, Management and Accounting 2 3%
Social Sciences 2 3%
Earth and Planetary Sciences 1 2%
Other 3 5%
Unknown 12 21%

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