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.
- 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
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|Size: ||3.1 MB|
|Publisher: ||Morgan Kaufmann|
|Date published: || 2014|
|ISBN: ||2370006353560 (DRM-EPUB)|
|Read Aloud: ||not allowed|