An Information Dispersal Algorithm Based Technique for Backup of Data in Cloud Data Centers
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Cloud computing is an emerging and popular networked environment these days. A lot of users take advantage of cloud service providers for various purposes. One such use of cloud computing is its use in taking backup of files provided by the users. The technique of replicating the file on multiple Data Centers is traditionally being used for this. However, this technique is very inefficient with respect to security and load balancing of the data because it increases the overall redundancy of the data. In this paper, we propose a technique which uses Information Dispersal Algorithms to take backup of file on the cloud. An Information Dispersal Algorithm takes a file F that needs to be dispersed among n nodes such that any m pieces are sufficient to reconstruct the whole file F. The size of each piece is |F/m|. It must also ensure that the complete knowledge of any m-1 pieces is insufficient to reconstruct the complete file F. For our proposed technique, we simulate a cloud environment using the CloudSim simulator and then use Information Dispersal Algorithms to take the backup of the required data. In this paper, we discuss the proposed technique and show how this technique provides a more secure, reliable and less redundant way to provide backup of data.
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“Google’s Approach to IT Security”, A Google White Paper. https://cloud.google.com/files/Google-CommonSecurity-WhitePaper-v1.4.pdf
A. Shamir, How to share a secret, Communications of the ACM, Vol. 22, pp. 612-613 1979.
G.R. Blakley, Safeguarding cryptographic key, National Computer Conference, pp. 313-317, 1979.
M. O. Rabin, Efficient dispersal of information for security, load balancing, and fault tolerance, Journal of the ACM, Vol. 36, pp. 335–348, 1989.
M. O. Rabin, The information dispersal algorithm and its applications, In Capocelli (Ed), Sequences: Combinatorics, Compression, Security, and Transmission, (New York: Springer-Verlag, 1990, 406-419).
R. Berlekampe, Algebraic Coding Theory (McGraw-Hill, 1968).
H. Krawczyk, Secret Sharing Made Short, Advances in Cryptology, (Berlin Heidelberg: Springer-Verlag, 1994, 136-146).
P. Beguin, A. Cresti, General information dispersal algorithms, Theoretical Computer Science, Vol. 209, pp. 87-105, 1998.
A. De Santis, B. Masucci, On Information Dispersal Algorithms, Proceedings of 2002 IEEE International Symposium on Information Theory - ISIT 2002, (Page: 410, Year of Publication: 2002 ISBN: 0-7803-7501-7).
H.M. Sun, S.P. Shieh, Optimal Information Dispersal for Reliable Communication in Computer Networks, Proceedings of International Conference on Parallel and Distributed Systems, (Page: 460-464, Year of Publication: 1994 ISBN: 0-8186-6555-6).
M. K. Nakayama and B. Yener, Optimal information dispersal for probabilistic latency targets, Computer Networks, Vol. 36, pp. 695-707, 2001.
A. Bestavros, An Adaptive Information Dispersal Algorithm for Time-Critical Reliable Communication, Network Management and Control, (US: Springer, 1994, 423-438).
A. Rahumed, H.C.H. Chen, Y. Tang, P.P.C. Lee and J.C.S. Lui, A Secure Cloud Backup System with Assured Deletion and Version Control, Proceedings of 40th International Conference on Parallel Processing Workshop (Page 160-167 Year Publication: 2011 ISBN: 978-1-4577-1337-8).
P. Ruggiero, M. A. Heckathorn, Data Backup Options, US-CERT, 2012. Available at http://www.us-cert.gov/sites/default/files/publications/data_backup_options.pdf. Accessed 01 Jan 2015.
K. Sharma, 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, n. 5, pp. 249-254, 2012.
Timothy Wood, Emmanuel Cecchet, K.K. Ramakrishnan, Prashant Shenoy, Jacobus van der Merwe, and Arun Venkataramani, Disaster Recovery as a Cloud Service: Economic Benefits & Deployment Challenges, Proceedings of the 2nd USENIX conference on Hot Topics in Cloud Computing, (Page 1-7, Year Publication: 2010).
G. Bell, C. Pistagna and S. Riccobene, Distributed backup through information dispersal, Electronic Notes in Theoretical Computer Science, Vol. 142, pp. 63-67, 2006.
Extend Enterprise File Services Beyond the Data Center; Mobilize Data Among Datacenters and Remote, Branch Offices, Hitachi Data Systems, 2012. http://www.hds.com/assets/pdf/hitachi-white-paper-data-mobility-solves-the-unstructured-data-dilemma.pdf
Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung, The Google file system, Proceedings of the nineteenth ACM symposium on Operating systems principles, (Page: 29-43, Year of Publication: 2003 ISBN: 1-58113-757-5).
R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. De Rose, R. Buyya, CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms, Software: Practice and Experience, Vol. 41, n. 1, pp. 23-50, 2011.
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