Cloud Computing: Data-Intensive Computing and Scheduling

Frederic Magoules, Jie Pan, Fei Teng

September 20, 2012 by Chapman and Hall/CRC
Reference - 231 Pages - 48 B/W Illustrations
ISBN 9781466507821 - CAT# K14685
Series: Chapman & Hall/CRC Numerical Analysis and Scientific Computing Series


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  • Discusses the implementation of priority-based strategies
  • Presents the elements underlying a cloud datacenter
  • Offers solutions to resource allocation problems in clouds
  • Describes the features of multidimensional data analysis queries
  • Illustrates the use of MapReduce, a new parallel programming model
  • Explores directions for further research


As more and more data is generated at a faster-than-ever rate, processing large volumes of data is becoming a challenge for data analysis software. Addressing performance issues, Cloud Computing: Data-Intensive Computing and Scheduling explores the evolution of classical techniques and describes completely new methods and innovative algorithms. The book delineates many concepts, models, methods, algorithms, and software used in cloud computing.

After a general introduction to the field, the text covers resource management, including scheduling algorithms for real-time tasks and practical algorithms for user bidding and auctioneer pricing. It next explains approaches to data analytical query processing, including pre-computing, data indexing, and data partitioning. Applications of MapReduce, a new parallel programming model, are then presented. The authors also discuss how to optimize multiple group-by query processing and introduce a MapReduce real-time scheduling algorithm.

A useful reference for studying and using MapReduce and cloud computing platforms, this book presents various technologies that demonstrate how cloud computing can meet business requirements and serve as the infrastructure of multidimensional data analysis applications.