Open Access   Article Go Back

A Survey on Data Recovery Approaches in Cloud Computing Environment

I. Benjamin Franklin1 , T.N. Ravi2

Section:Survey Paper, Product Type: Journal Paper
Volume-6 , Issue-5 , Page no. 440-447, May-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i5.440447

Online published on May 31, 2018

Copyright © I. Benjamin Franklin, T.N. Ravi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: I. Benjamin Franklin, T.N. Ravi, “A Survey on Data Recovery Approaches in Cloud Computing Environment,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.440-447, 2018.

MLA Style Citation: I. Benjamin Franklin, T.N. Ravi "A Survey on Data Recovery Approaches in Cloud Computing Environment." International Journal of Computer Sciences and Engineering 6.5 (2018): 440-447.

APA Style Citation: I. Benjamin Franklin, T.N. Ravi, (2018). A Survey on Data Recovery Approaches in Cloud Computing Environment. International Journal of Computer Sciences and Engineering, 6(5), 440-447.

BibTex Style Citation:
@article{Franklin_2018,
author = {I. Benjamin Franklin, T.N. Ravi},
title = {A Survey on Data Recovery Approaches in Cloud Computing Environment},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {6},
Issue = {5},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {440-447},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2001},
doi = {https://doi.org/10.26438/ijcse/v6i5.440447}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i5.440447}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2001
TI - A Survey on Data Recovery Approaches in Cloud Computing Environment
T2 - International Journal of Computer Sciences and Engineering
AU - I. Benjamin Franklin, T.N. Ravi
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 440-447
IS - 5
VL - 6
SN - 2347-2693
ER -

VIEWS PDF XML
913 417 downloads 250 downloads
  
  
           

Abstract

Cloud computing system provides a lot of convenient computational and data storage services to the users. Data transfer to the cloud environment is convenient. The cloud computing system generates a large amount of private data on the main cloud. Then, the need of data recovery services are increasing day-by-day and require development of efficient data recovery technique. The aim of the data recovery technique is to collect the information from the backup server, when the server lost the data and unable to provide the data to the user. Various techniques are proposed for efficient recovery of data. This paper focuses on the comprehensive review of the data recovery approaches, issues in data recovery, failures in cloud storage, key factors and their role in data recovery and existing data security technologies in the cloud. The main objective of the review paper is to summarize the prevailing data recovery techniques in the cloud computing domain.

Key-Words / Index Term

Cloud Computing, Cloud Storage, Data Recovery, Data Security, Data Storage Service, Private Data

References

[1] Z. Ke, W. Hua, and L. Chunhua, "Cloud storage technology and its applications," ed, 2012.
[2] Z. Jian-Hua and Z. Nan, "Cloud computing-based data storage and disaster recovery," in Future Computer Science and Education (ICFCSE), 2011 International Conference on, 2011, pp. 629-632.
[3] C. Modi, D. Patel, B. Borisaniya, A. Patel, and M. Rajarajan, "A survey on security issues and solutions at different layers of Cloud computing," The journal of supercomputing, vol. 63, pp. 561-592, 2013.
[4] S. Subashini and V. Kavitha, "A survey on security issues in service delivery models of cloud computing," Journal of network and computer applications, vol. 34, pp. 1-11, 2011.
[5] J. Wang, Y. Zhao, S. Jiang, and J. Le, "Providing privacy preserving in cloud computing," in Human System Interactions (HSI), 2010 3rd Conference on, 2010, pp. 472-475.
[6] M. Mowbray and S. Pearson, "A client-based privacy manager for cloud computing," in Proceedings of the fourth international ICST conference on COMmunication system softWAre and middlewaRE, 2009, p. 5.
[7] D. Lin and A. Squicciarini, "Data protection models for service provisioning in the cloud," in Proceedings of the 15th ACM symposium on Access control models and technologies, 2010, pp. 183-192.
[8] M. R. Abbasy and B. Shanmugam, "Enabling data hiding for resource sharing in cloud computing environments based on DNA sequences," in IEEE World Congress on Services (SERVICES), 2011, pp. 385-390.
[9] S. J. Stolfo, M. B. Salem, and A. D. Keromytis, "Fog computing: Mitigating insider data theft attacks in the cloud," in Security and Privacy Workshops (SPW), 2012 IEEE Symposium on, 2012, pp. 125-128.
[10] R. P. Sarang and R. K. Bunkar, "Study of Services and Privacy Usage in Cloud Computing," International Journal of Scientific Research in Computer Science and Engineering, vol. 1, pp. 7-12, 2013.
[11] Vishal Kadam and M. Kumbhkar, "Security in Cloud Environment," International Journal of Scientific Research in Computer Science and Engineering vol. 2, pp. 6-10, 2014.
[12] A. Bala and Y. Osais, "Modelling and simulation of DDOS Attack using SimEvents," International Journal of Scientific Research in Network Security and Communication, vol. 1, pp. 5-14, 2013.
[13] K. Sharma and K. R. Singh, "Seed block algorithm: a remote smart data back-up technique for cloud computing," in International Conference on Communication Systems and Network Technologies (CSNT), 2013, pp. 376-380.
[14] R. Gandhi and M. Seshaiah, "Data back-up and recovery techniques for cloud server using seed block algorithm," International Journal of Engineering Research and Applications, vol. 5, pp. 91-95, 2015.
[15] M. Shaikh, A. Achary, S. Menon, and N. Konar, "Improving cloud data storage using data partitioning and data recovery using seed block algorithm," International Journal of Latest Technology in Engineering, Management & Applied Science, vol. 4, 2015.
[16] K. Pophale, P. Patil, R. Shelake, and S. Sapkal, "Seed Block Algorithm: Remote Smart Data-Backup Technique for Cloud Computing," International Journal of Advanced Research in Computer and Communication Engineering, vol. 4, 2015.
[17] M. Tidke, V. Jadhav, S. Parab, S. Patil, Y. Patil, U. Scholar, et al., "Seed Block Algorithm: A New Approach for Data Back-up and Recovery in Cloud Computing," International Journal of Engineering Science, vol. 4093, 2016.
[18] C.-w. Song, S. Park, D.-w. Kim, and S. Kang, "Parity cloud service: a privacy-protected personal data recovery service," in Trust, Security and Privacy in Computing and Communications (TrustCom), 2011 IEEE 10th International Conference on, 2011, pp. 812-817.
[19] H. Jung, Y. Park, C.-W. Song, and S. Kang, "PCS: a parity-based personal data recovery service in cloud," Cluster Computing, vol. 20, pp. 2655-2668, 2017.
[20] S. Zhang, H. Zhou, Y. Yang, and Z. Wu, "A joint Bloom Filter and cross-encoding for data verification and recovery in cloud," in Computers and Communications (ISCC), 2017 IEEE Symposium on, 2017, pp. 614-619.
[21] A. Singh, S. Garg, S. Batra, N. Kumar, and J. J. Rodrigues, "Bloom filter based optimization scheme for massive data handling in IoT environment," Future Generation Computer Systems, 2017.
[22] Y. Ueno, N. Miyaho, S. Suzuki, and K. Ichihara, "Performance evaluation of a disaster recovery system and practical network system applications," in Systems and Networks Communications (ICSNC), 2010 Fifth International Conference on, 2010, pp. 195-200.
[23] S. Suguna and A. Suhasini, "Overview of data backup and disaster recovery in cloud," in International Conference on Information Communication and Embedded Systems (ICICES), 2014, pp. 1-7.
[24] G. Pirro, P. Trunfio, D. Talia, P. Missier, and C. Goble, "Ergot: A semantic-based system for service discovery in distributed infrastructures," in Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, 2010, pp. 263-272.
[25] B. Solanki and J. Jha, "Web Service Discovery using Relational Database and Apache Lucene," 2015.
[26] J. Jayalakshmi and G. Mathuramgbigai, "A SURVEY ON BACKUP RECOVERY ISSUES IN CLOUD COMPUTING," 2017.
[27] V. Javaraiah, "Backup for cloud and disaster recovery for consumers and SMBs," in Advanced Networks and Telecommunication Systems (ANTS), 2011 IEEE 5th International Conference on, 2011, pp. 1-3.
[28] K. Bangale, K. Nadhe, N. Gupta, S. S. Parihar, and G. Mankar, "Smart Remote Health Care Data Collection Server," International Journal of Computer Science and Mobile Computing, vol. 3, pp. 415-422, 2014.
[29] M. Assefi, M. Wittie, and A. Knight, "Impact of network performance on cloud speech recognition," in Computer Communication and Networks (ICCCN), 2015 24th International Conference on, 2015, pp. 1-6.
[30] L. Sun, J. An, Y. Yang, and M. Zeng, "Recovery strategies for service composition in dynamic network," in Cloud and Service Computing (CSC), 2011 International Conference on, 2011, pp. 60-64.
[31] D. Niu, L. Rui, C. Zhong, and X. Qiu, "A composition and recovery strategy for mobile social network service in disaster," The Computer Journal, vol. 58, pp. 700-708, 2015.
[32] M. G. Narke, M. A. Harijan, M. A. Shinde, and H. Sonawane, "A smart data backup technique for cloud computing using seed block algorithm strategy," 2015.
[33] M. Raje and D. Mukhopadhyay, "Algorithm for Back-Up and Recovery of Data Stored on Cloud along with Authentication of the User," in Information Technology (ICIT), 2015 International Conference on, 2015, pp. 175-180.
[34] D. Niu, L. Rui, H. Huang, and X. Qiu, "A service recovery method based on trust evaluation in mobile social network," Multimedia Tools and Applications, vol. 76, pp. 3255-3277, 2017.
[35] M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. H. Katz, A. Konwinski, et al., "Above the clouds: A berkeley view of cloud computing," Technical Report UCB/EECS-2009-28, EECS Department, University of California, Berkeley2009.
[36] S. Vishwakarma and P. D. Soni, "Cloud Mirroring: A Technique of Data Recovery," International Journal of Current Engineering and Technology, vol. 5, 2015.
[37] T. Kulkarni, K. Dhaygude, S. Memane, and O. Nene, "Intelligent Cloud Back-Up System," International Journal of Emerging Engineering Research and Technology, vol. 2, pp. 82-89, 2014.
[38] S. Agalya, S. Bhavithra, and S. S. Benitta, "AN INTELLIGENT DATA BACK-UP AND RETRIEVING TECHNIQUE FOR CLUSTER ENVIRONMENT," Journal of Engineering And Technology Research, vol. 3, pp. 1-9, 2015.
[39] B. Cully, G. Lefebvre, D. Meyer, M. Feeley, N. Hutchinson, and A. Warfield, "Remus: High availability via asynchronous virtual machine replication," in Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation, 2008, pp. 161-174.
[40] K. Sharma and K. R. Singh, "Online data back-up and disaster recovery techniques in cloud computing: A review," International Journal of Engineering and Innovative Technology (IJEIT), vol. 2, pp. 249-254, 2012.
[41] K. Keahey, M. Tsugawa, A. Matsunaga, and J. Fortes, "Sky computing," IEEE Internet Computing, vol. 13, pp. 43-51, 2009.
[42] M. Wiboonrat, "An empirical IT contingency planning model for disaster recovery strategy selection," in Engineering Management Conference, 2008. IEMC Europe 2008. IEEE International, 2008, pp. 1-5.
[43] J. Che, Y. Duan, T. Zhang, and J. Fan, "Study on the security models and strategies of cloud computing," Procedia Engineering, vol. 23, pp. 586-593, 2011.
[44] M. Wiboonrat, "System reliability of fault tolerant data center," in The Fifth International Conference on Communication Theory, Reliability, and Quality of Service, Chamonix, France, 2012, pp. 19-25.
[45] R. Singha, "A multi-site disaster recovery solution based on ip storage networking," in International Conference on Information and Computer Networks, 2012, pp. 139-142.
[46] M. Wiboonrat and K. Kosavisutte, "Optimization strategy for disaster recovery," in Management of Innovation and Technology, 2008. ICMIT 2008. 4th IEEE International Conference on, 2008, pp. 675-680.
[47] D. Bermbach, M. Klems, S. Tai, and M. Menzel, "Metastorage: A federated cloud storage system to manage consistency-latency tradeoffs," in IEEE International Conference on Cloud Computing (CLOUD), 2011, pp. 452-459.
[48] O. H. Alhazmi and Y. K. Malaiya, "Evaluating disaster recovery plans using the cloud," in Reliability and Maintainability Symposium (RAMS), 2013 Proceedings-Annual, 2013, pp. 1-6.
[49] F. Xiang, C. Liu, and B. Fang, "Novel “rich cloud” based data disaster recovery strategy," J. Commun, vol. 6, pp. 92-101, 2013.
[50] T. Wood, E. Cecchet, K. K. Ramakrishnan, P. J. Shenoy, J. E. van der Merwe, and A. Venkataramani, "Disaster Recovery as a Cloud Service: Economic Benefits & Deployment Challenges," HotCloud, vol. 10, pp. 8-15, 2010.
[51] G. Aceto, A. Botta, W. De Donato, and A. Pescapè, "Cloud monitoring: A survey," Computer Networks, vol. 57, pp. 2093-2115, 2013.