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Survey on Data Deduplication for Cloud Storage to Reduce Fragmentation

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Reshma A. Fegade, R. D. Bharati
10.5120/ijca2016907942

Reshma A Fegade and R D Bharati. Article: Survey on Data Deduplication for Cloud Storage to Reduce Fragmentation. International Journal of Computer Applications 134(5):14-17, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Reshma A. Fegade and R. D. Bharati},
	title = {Article: Survey on Data Deduplication for Cloud Storage to Reduce Fragmentation},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {134},
	number = {5},
	pages = {14-17},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Data Deduplication is an important technique which provides better result to store more information with less space. Cost and maintenance of Information backup storage system for major enterprises can be minimized by storing it on Cloud Storage. Data redundancy between different kinds of data storage gets minimal by utilizing data deduplication method. By giving each application differently and storing the associated information distinctly the overall disk usage can be enhanced to a great level. Cloud backup systems uses data deduplication to eliminate duplicate chunks that are present in multiple files. The duplicate chunks are substituted with the references to already present chunks through deduplication, without storing it again on cloud storage. The successive chunks are actually stored in scattered form in backup system in numerous segments (the storage unit of cloud).

References

  1. Fu, Min, et al. "Reducing Fragmentation for In-line Deduplication Backup Storage via Exploiting Backup History and Cache Knowledge."
  2. Gharaibeh, Abdullah, et al. "CloudDT: efficient tape resource management using deduplication in cloud backup and archival services." Proceedings of the 8th International Conference on Network and Service Management. International Federation for Information Processing, 2012.
  3. http://viewer.media.bitpipe.com/1019054049_245/1240950275_886/FalconStor_sDataBackup_Final.pdf
  4. Lai, Rongyu, et al. "A Near-Exact Defragmentation Scheme to Improve Restore Performance for Cloud Backup Systems." Algorithms and Architectures for Parallel Processing. Springer International Publishing, 2014. 457-471.
  5. Mkandawire, Stephen. "Improving Backup and Restore Performance for Deduplication-based Cloud Backup Services." (2012).
  6. Muthitacharoen, Athicha, Benjie Chen, and David Mazieres. "A low-bandwidth network file system." ACM SIGOPS Operating Systems Review. Vol. 35. No. 5. ACM, 2001.
  7. Nam, Youngjin, et al. "Chunk fragmentation level: An effective indicator for read performance degradation in deduplication storage." High Performance Computing and Communications (HPCC), 2011 IEEE 13th International Conference on. IEEE, 2011.
  8. Nam, Young Jin, Dongchul Park, and David HC Du. "Assuring demanded read performance of data deduplication storage with backup datasets." Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS), 2012 IEEE 20th International Symposium on. IEEE, 2012.
  9. Paulo, João, and José Pereira. "A survey and classification of storage deduplication systems." ACM Computing Surveys (CSUR) 47.1 (2014): 11.

Keywords

Cloud Backup, Data deduplication, Fragmentation.