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Cloud Computing: Data-Intensive Computing and Scheduling book cover

1st Edition

Cloud Computing Data-Intensive Computing and Scheduling

By Frederic Magoules, Jie Pan, Fei Teng Copyright 2013
232 Pages
by Chapman & Hall

232 Pages
by Chapman & Hall

231 Pages
by Chapman & Hall
Also available as eBook on:
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,... Read more

Overview of Cloud Computing. Resource Scheduling for Cloud Computing. Game Theoretical Allocation in a Cloud Datacenter. Multidimensional Data Analysis in a Cloud Datacenter. Data-Intensive Applications with MapReduce. Large-Scale Multidimensional Data Aggregation. Multidimensional Data Analysis Optimization. Real-Time Scheduling with MapReduce. Future for Cloud Computing. Bibliography. Index.

Biography

Frédéric Magoulès is a professor at École Centrale Paris, where he leads the high performance computing research group. His research focuses on the algorithmic interface between parallel computing and the numerical analysis of PDEs and algebraic differential equations. He earned a Ph.D. in applied mathematics from Université Pierre et Marie Curie.



Jie Pan is a Java developer at the Klee Group Company. She earned a Ph.D. in applied mathematics. During her doctoral work, she focused on large-scale data analysis on distributed systems.



Fei Teng is a researcher in the Key Lab of Cloud Computing and Intelligent Technology at Southwest Jiaotong University. Her research interests are mainly in cloud computing, data mining, resource allocation, and distributed scheduling algorithms.

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