Energy Efficiency in Data Centers and Clouds
- 1st Edition, Volume 100 - January 26, 2016
- Latest edition
- Editors: Suyel Namasudra, Hamid Sarbazi-Azad
- Language: English
Advances in Computers carries on a tradition of excellence, presenting detailed coverage of innovations in computer hardware, software, theory, design, and applicati… Read more
Advances in Computers carries on a tradition of excellence, presenting detailed coverage of innovations in computer hardware, software, theory, design, and applications.
The book provides contributors with a medium in which they can explore their subjects in greater depth and breadth than journal articles typically allow.
The articles included in this book will become standard references, with lasting value in this rapidly expanding field.
- Presents detailed coverage of recent innovations in computer hardware, software, theory, design, and applications
- Includes in-depth surveys and tutorials on new computer technology pertaining to computing: combinatorial testing, constraint-based testing, and black-box testing
- Written by well-known authors and researchers in the field
- Includes extensive bibliographies with most chapters
- Presents volumes devoted to single themes or subfields of computer science
Researchers in high performance computer areas, hardware manufacturers, educational programs in physics and scientific computation and in computer science.
Chapter One: Power Management in Data Centers: Cost, Sustainability, and Demand Response
- Abstract
- 1 Introduction
- 2 Cost Minimization in Data Centers
- 3 Sustainability: Water Efficiency
- 4 Sustainability: Exploiting Temporal Diversity of Water Efficiency (WACE)
- 5 Sustainability: Optimizing Water Efficiency in Distributed Data Centers (GLB-WS)
- 6 Demand Response of Geo-Distributed Data Centers: Real-Time Pricing Game Approach
- 7 Demand Response of Colocation Data Centers: A Reverse Auction Approach
- 8 Conclusion and Open Challenges
- Acknowledgments
Chapter Two: Energy-Efficient Big Data Analytics in Datacenters
- Abstract
- 1 Introduction
- 2 Datacenter and Cloud Computing
- 3 Handling Big Data on Cloud-Based Datacenters
- 4 Energy Efficiency in Datacenters for Big Data Analytics
- 5 Trends for the Big Data Analytics in Cloud-Based Datacenters
- 6 Summary
Chapter Three: Energy-Efficient and SLA-Based Resource Management in Cloud Data Centers
- Abstract
- 1 Introduction
- 2 Energetic Characterization of a Data Center
- 3 Cloud Computing Environments
- 4 Constraints to Energy Efficiency in Cloud Data Centers
- 5 Current Resource Management in Cloud Data Centers
- 6 A Practical Case of Energy-Efficient and SLA-Based Management of Resources
- 7 Conclusions and Open Challenges
Chapter Four: Achieving Energy Efficiency in Datacenters by Virtual Machine Sizing, Replication, and Placement
- Abstract
- 1 Introduction
- 2 Related Work in Datacenter Power and Resource Management
- 3 System Model
- 4 Problem Formulation
- 5 Proposed Algorithm
- 6 Simulation Results
- 7 Conclusion and Future Research Direction
Chapter Five: Communication-Awareness for Energy-Efficiency in Datacenters
- Abstract
- 1 Introduction
- 2 Power Consuming Components in Networks
- 3 Energy Reduction Techniques
- 4 Our Approach
- 5 Problem Formulation and Algorithms
- 6 Experimental Results
- 7 Conclusion and Future Work
- Acknowledgments
- Edition: 1
- Latest edition
- Volume: 100
- Published: January 26, 2016
- Language: English
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Suyel Namasudra
Suyel Namasudra has received Ph.D. degree from the National Institute of Technology Silchar, Assam, India. He was a post-doctorate fellow at the International University of La Rioja (UNIR), Spain. Currently, Dr. Namasudra is working as an assistant professor in the Department of Computer Science and Engineering at the National Institute of Technology Agartala, Tripura, India. Before joining the National Institute of Technology Agartala, Dr. Namasudra was an assistant professor in the Department of Computer Science and Engineering at the National Institute of Technology Patna, Bihar, India. His research interests include blockchain technology, cloud computing, DNA computing, and information security. Dr. Namasudra has edited 7 books, 5 patents, and 85 publications in conference proceedings, book chapters, and refereed journals like IEEE TII, IEEE TCE, IEEE T-ITS, IEEE TSC, IEEE TCSS, IEEE TCBB, ACM TOMM, ACM TOSN, ACM TALLIP, FGCS, CAEE, and many more. He is the Editor-in-Chief of the Cloud Computing and Data Science (ISSN: 2737-4092 (online)) journal. Dr. Namasudra has served as a Lead Guest Editor/Guest Editor in many reputed journals like IEEE TCE (IEEE, IF: 4.3), IEEE TBD (IEEE, IF: 7.2), ACM TOMM (ACM, IF: 3.144), MONET (Springer, IF: 3.426), CAEE (Elsevier, IF: 3.818), CAIS (Springer, IF: 4.927), CMC (Tech Science Press, IF: 3.772), Sensors (MDPI, IF: 3.576), and many more. He has also participated in many international conferences as an organizer and session chair. Dr. Namasudra is a senior member of IEEE, and a member of ACM and IEI. He has been featured in the list of the top 2% scientists in the world in 2021, 2022, and 2023. His h-index is 37.
Affiliations and expertise
Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, IndiaHS
Hamid Sarbazi-Azad
Hamid Sarbazi-Azad is currently a professor of computer science and engineering at Sharif University of Technology, and a research professor of computer science at the Institute for Research in Fundamental Sciences, both in Tehran, Iran . His research interests include high-performance computer/memory architectures, NoCs and SoCs, learning architectures,, social networks, and storage systems, on which he has published over 400 refereed papers. He received Khwarizmi International Award in 2006, TWAS Young Scientist Award in engineering sciences in 2007, and Sharif University Distinguished Researcher awards in years 2004, 2007, 2008, 2010 and 2013. He is now an associate editor of ACM Computing Surveys, IEEE Computer Architecture Letters, and Elsevier’s Computers and Electrical Engineering.
Affiliations and expertise
Sharif University of Technology, Tehran, IranRead Energy Efficiency in Data Centers and Clouds on ScienceDirect