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2012 IEEE Fifth International Conference on Cloud Computing
Multi-level Selective Deduplication for VM Snapshots in Cloud Storage
Honolulu, HI, USA USA
June 24-June 29
ISBN: 978-1-4673-2892-0
In a virtualized cloud computing environment, frequent snapshot backup of virtual disks improves hosting reliability but storage demand of such operations is huge. While dirty bit-based technique can identify unmodified data between versions, full deduplication with fingerprint comparison can remove more redundant content at the cost of computing resources. This paper presents a multi-level selective deduplication scheme which integrates inner-VM and cross-VM duplicate elimination under a stringent resource requirement. This scheme uses popular common data to facilitate fingerprint comparison while reducing the cost and it strikes a balance between local and global deduplication to increase parallelism and improve reliability. Experimental results show the proposed scheme can achieve high deduplication ratio while using a small amount of cloud resources.
Index Terms:
Indexes,Distributed databases,Image segmentation,Memory management,Fault tolerance,Fault tolerant systems,Distributed data deduplication,Cloud storage backup,Virtual machine snap-shots
Citation:
Wei Zhang, Hong Tang, Hao Jiang, Tao Yang, Xiaogang Li, Yue Zeng, "Multi-level Selective Deduplication for VM Snapshots in Cloud Storage," cloud, pp.550-557, 2012 IEEE Fifth International Conference on Cloud Computing, 2012
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