Reliability Assurance of Big Data in the Cloud
1st Edition
Cost-Effective Replication-Based Storage
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Description
With the rapid growth of Cloud computing, the size of Cloud data is expanding at a dramatic speed. A huge amount of data is generated and processed by Cloud applications, putting a higher demand on cloud storage. While data reliability should already be a requirement, data in the Cloud needs to be stored in a highly cost-effective manner. This book focuses on the trade-off between data storage cost and data reliability assurance for big data in the Cloud. Throughout the whole Cloud data lifecycle, four major features are presented: first, a novel generic data reliability model for describing data reliability in the Cloud; second, a minimum replication calculation approach for meeting a given data reliability requirement to facilitate data creation; third, a novel cost-effective data reliability assurance mechanism for big data maintenance, which could dramatically reduce the storage space needed in the Cloud; fourth, a cost-effective strategy for facilitating data creation and recovery, which could significantly reduce the energy consumption during data transfer.
Key Features
- Captures data reliability with variable disk rates and compares virtual to physical disks
- Offers methods for reducing cloud-based storage cost and energy consumption
- Presents a minimum replication benchmark for data reliability requirements to evaluate various replication-based data storage approaches
Readership
Researchers, educators, and practitioners in the area of Cloud computing, Cloud storage and distributed computing
Table of Contents
- About the Authors
- Preface
- Acknowledgments
- 1: Introduction
- Abstract
- 1.1. Data reliability in the Cloud
- 1.2. Background of Cloud storage
- 1.3. Key issues of research
- 1.4. Book overview
- 2: Literature review
- Abstract
- 2.1. Data reliability assurance in hardware
- 2.2. Data reliability assurance in software
- 2.3. Data transfer for distributed systems
- 2.4. Summary
- 3: Motivating example and problem analysis
- Abstract
- 3.1. Motivating example
- 3.2. Problem analysis
- 3.3. Summary
- 4: Generic data reliability model in the cloud
- Abstract
- 4.1. Properties of the data reliability model
- 4.2. Generic data reliability model
- 4.3. Summary
- 5: Minimum replication for meeting the data reliability requirement
- Abstract
- 5.1. The minimum replication calculation approach
- 5.2. Minimum replication benchmark
- 5.3. Evaluation of the minimum replication calculation approach
- 5.4. Summary
- 6: Cost-effective data reliability assurance for data maintenance
- Abstract
- 6.1. Proactive replica checking
- 6.2. Overview of PRCR
- 6.3. Working process of PRCR
- 6.4. Optimization algorithms in PRCR
- 6.5. Evaluation of PRCR
- 6.6. Summary
- 7: Cost-effective data transfer for data creation and data recovery
- Abstract
- 7.1. Determining the deadline for data creation and data recovery
- 7.2. Cloud network model
- 7.3. Energy consumption model for Cloud data transfer
- 7.4. Novel cost-effective data transfer strategy LRCDT
- 7.5. Evaluation of LRCDT
- 7.6. Summary
- 8: Conclusions and future work
- Abstract
- 8.1. Summary of this book
- 8.2. Key contributions of this book
- 8.3. Further discussion and future work
- Bibliography
- Appendix
- Index
Details
- No. of pages:
- 106
- Language:
- English
- Copyright:
- © Morgan Kaufmann 2015
- Published:
- 10th December 2014
- Imprint:
- Morgan Kaufmann
- Paperback ISBN:
- 9780128025727
- eBook ISBN:
- 9780128026687
About the Authors

Yun Yang
Yun Yang is currently a full professor in School of Software and Electrical Engineering at Swinburne University of Technology, Melbourne, Australia. Prior to joining Swinburne in 1999 as an associate professor, he was a lecturer and senior lecturer at Deakin University, Australia, during 1996-1999. He has coauthored four books and published over 200 papers in journals and refereed conference proceedings. He is currently on the Editorial Board of IEEE Transactions on Cloud Computing. His current research interests include software technologies, cloud computing, p2p/grid/cloud workflow systems, and service-oriented computing.
Affiliations and Expertise
Swinburne University of Technology, Melbourne, Australia
Wenhao Li
Wenhao Li is currently a research fellow in School of Software and Electrical Engineering at Swinburne University of Technology, Melbourne, Australia. His research interests include parallel and distributed computing, cloud and grid computing, workflow technologies, and data management in distributed computing environment.
Affiliations and Expertise
Swinburne University of Technology, Melbourne, Australia

Dong Yuan
Dong Yuan is currently a research fellow in School of Software and Electrical Engineering at Swinburne University of Technology, Melbourne, Australia. His research interests include data management in parallel and distributed systems, scheduling and resource management, grid and cloud computing.
Affiliations and Expertise
Swinburne University of Technology, Melbourne, Australia
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