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Cloud Computing : Data-Intensive Computing and Scheduling / Frederic Magoules , Jie Pan , Fei Teng

By: Contributor(s): Material type: TextTextLanguage: English Series: Chapman & Hall/CRC numerical analysis and scientific computing seriesPublication details: Boca Raton : CRC Press , 2012Description: xxiii, 205 Pages : illustrations ; 24 cmISBN:
  • 9781466507821 (hardback)
Subject(s): LOC classification:
  • QA76.585 .M34 2012
Summary: "This practical book delves into new cloud computing technologies and indicates the main challenges for their development in the future, especially for resource management problems. By systematizing cloud resource management problems, it helps knowledgeable readers who are not subject matter experts in a topic but want to have an in-depth analysis. It provides a parallel programming model, MapReduce, to parallelize multidimensional analytical query processing. The text includes how to master the fundamental concepts and programming models and apply them successfully to reach objectives. The authors discuss how to maximize the value of existing scheduling algorithms from a theoretical point of view"-- Provided by publisher
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Item type Current library Call number Copy number Status Barcode
Books Books Fayza Aboulnaga Central Library | مكتبة فايزة أبو النجا المركزية بالحرم الجامعي QA76.585 .M34 2012 (Browse shelf(Opens below)) C. 1 Available 10005999

Includes bibliographical references (Pages 187-202) and index

"This practical book delves into new cloud computing technologies and indicates the main challenges for their development in the future, especially for resource management problems. By systematizing cloud resource management problems, it helps knowledgeable readers who are not subject matter experts in a topic but want to have an in-depth analysis. It provides a parallel programming model, MapReduce, to parallelize multidimensional analytical query processing. The text includes how to master the fundamental concepts and programming models and apply them successfully to reach objectives. The authors discuss how to maximize the value of existing scheduling algorithms from a theoretical point of view"-- Provided by publisher

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