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Optimized Cloud Resource Management and Scheduling: Theories and Practices
     

Optimized Cloud Resource Management and Scheduling: Theories and Practices

by Wenhong Dr. Tian, Yong Dr. Zhao
 

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Optimized Cloud Resource Management and Scheduling identifies research directions and technologies that will facilitate efficient management and scheduling of computing resources in cloud data centers supporting scientific, industrial, business, and consumer applications. It serves as a valuable reference for systems architects, practitioners, developers,

Overview

Optimized Cloud Resource Management and Scheduling identifies research directions and technologies that will facilitate efficient management and scheduling of computing resources in cloud data centers supporting scientific, industrial, business, and consumer applications. It serves as a valuable reference for systems architects, practitioners, developers, researchers and graduate level students.

  • Explains how to optimally model and schedule computing resources in cloud computing
  • Provides in depth quality analysis of different load-balance and energy-efficient scheduling algorithms for cloud data centers and Hadoop clusters
  • Introduces real-world applications, including business, scientific and related case studies
  • Discusses different cloud platforms with real test-bed and simulation tools

Editorial Reviews

From the Publisher
"This book offers an excellent overview of the state-of-the-art in resource scheduling and management in cloud computing. I strongly recommend the book as a reference for system architects, practitioners, developers, researchers and graduate level students." —Rajkumar Buyya, Editor in Chief, IEEE Transactions on Cloud Computing

Product Details

ISBN-13:
9780128014769
Publisher:
Elsevier Science
Publication date:
10/30/2014
Pages:
284
Product dimensions:
6.00(w) x 8.90(h) x 0.70(d)

Meet the Author

Dr. Wenhong Tian has a PhD from Computer Science Department of North Carolina State University(NCSU) and did post-doc with joint funding from Ork Ridge National Lab and NCSU. He is now an associate professor at University of Electronic Science and Technology of China. His research interests include modeling and performance analysis of communication networks, Cloud computing and bio-computing. He has published more than 40 journal /conference papers in related areas.

Prof. Yong Zhao has a PhD from Computer Science Department of Chicago University (under supervising of Prof. Ian Foster); his is now a professor at University of Electronic Science and Technology of China. His research interests include Grid computing, large-data process in Cloud computing etc. He published about 30 journal and conference papers in related areas.

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