Efficient and Reliable Data Recovery Technique in Cloud Computing

Praveen S. Challagidad; Ambika S. Dalawai; Mahantesh N. Birje

doi:doi:10.11648/j.iotcc.s.2017050501.13

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Efficient and Reliable Data Recovery Technique in Cloud Computing

Praveen S. Challagidad, Ambika S. Dalawai, Mahantesh N. Birje

Published in Internet of Things and Cloud Computing (Volume 5, Issue 5-1)

Received: 4 July 2017 Accepted: 5 July 2017 Published: 25 August 2017

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Abstract

Cloud computing provides accessing of any kind of services dynamically over Internet on demand basis. One of the most significant service that is being provided is storage as a service. Cloud customer can store any amount of data into cloud storage results to huge amount of data at the datacenter. The data may get deleted by man-made disaster (either CSP or customer itself without their knowledge) or by natural disasters (either earth quakes or volcanoes) from the datacenters. Nowadays, data has been generated in large quantity that requires the data recovery services or techniques. Therefore there is a requirement for designing an efficient data recovery technique to recover the lost data. Many researchers have proposed different data recovery techniques but they lack in efficiency and reliability. In this paper, a multi-server system based on Enriched Genetic Algorithm to recover the lost data by using four cloud backup servers is discussed. To achieve reliability the proposed technique provides the flexibility for the user to collect information from any backup server when main cloud server loses its data and is unable to provide data to users.

Published in	Internet of Things and Cloud Computing (Volume 5, Issue 5-1) This article belongs to the Special Issue Advances in Cloud and Internet of Things
DOI	10.11648/j.iotcc.s.2017050501.13
Page(s)	13-18
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Cloud Computing, Data Recovery, Backup, Data Restore

References

[1]	Mahantesh N. Birje, Praveen S. Challagidad, “Cloud computing review: concepts, technology, challenges and security”, International Journal of Cloud Computing, InderScience Publishers, vol. 6, issue 1, 2017.
[2]	P. S. Challagidad, M. N. Birje, “Hierarchical Attribute-based Access Control with Delegation Approach in Cloud”, Proceedings of the 11th INDIACom; INDIACom-2017; IEEE Conference ID: 40353 2017 4th International Conference on “Computing for Sustainable Global Development”, 01st - 03rd March, 2017.
[3]	Greeshma Radhakrishnan, Chenni Kumaran, “DR – Cloud: Multi- Cloud Based Disaster Recovery Service”, International Journal of Innovative Research in Science, Engineering and Technology, Vol. 5, Issue 3, March 2016.
[4]	Megha Rani Raigonda, Tahseen Fatima, “A Cloud Based Automatic Recovery and Backup System with Video Compression”, International Journal of Engineering and Computer Science, ISSN: 2319-7242, Vol. 5, Issue 09, and September 2016.
[5]	Tanay Kulkarni, Sumit Memane, “Intelligent Cloud Security Back-Up System”, International Journal of Technical Research and Applications, Vol. 3, Issue 2, Mar-Apr 2015.
[6]	M. N. Birje, P. S. Challagidad, M. T. Tapale, R. H. Goudar, “Security Issues and Countermeasures in Cloud Computing”, International Journal of Applied Engineering Research, ISSN 0973- 4562, Vol. 10, No. 86, 2015.
[7]	Shilpi U. Vishwakarma and Praveen D. Soni, “Cloud Mirroring: A Technique of Data Recovery”, International Journal of Current Engineering and Technology, Vol. 5, No. 2, March 2015.
[8]	PS. Vijayabaskaran, “Efficient Backing up Data for Migrating Cloud to Cloud”, International Journal of Computer Science and Information Technologies, Vol. 6, 2015.
[9]	Atesh Kumar, Saurabh Mishra, “Priority with Adoptive Data Migration in Case of Disaster using Cloud Computing use style”, International Conference on Communication, Information & Computing Technology, 2015.
[10]	Ruchira. H. Titare, Prof. Pravin Kulurkar, “Remote Data Back-up and Privacy Preserving Data Distribution in the Cloud: A Review”, International Journal of Computer Science and Mobile Applications, Vol. 2, Issue. 11, November 2014.
[11]	Jian Wan, Huijia Xuan, “Research and Implementation of Distributed Disaster Recovery System Based on PRS Algorithm”, International Journal of Database Theory and Application, Vol. 7, No. 3, 2014.
[12]	Chintureena Thingom, “A Study on Tools for Cloud Disaster Management”, International Journal of Interdisciplinary and Multidisciplinary Studies, 2014.
[13]	Kolipaka Kiran, Janapati Venkata Krishna, “Smart Data Back-up Technique for Cloud Computing using Secure Erasure Coding”, International Journal of Computer Trends and Technology, vol. 16, number 3 – Oct 2014.

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APA Style

Praveen S. Challagidad, Ambika S. Dalawai, Mahantesh N. Birje. (2017). Efficient and Reliable Data Recovery Technique in Cloud Computing. Internet of Things and Cloud Computing, 5(5-1), 13-18. https://doi.org/10.11648/j.iotcc.s.2017050501.13

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ACS Style

Praveen S. Challagidad; Ambika S. Dalawai; Mahantesh N. Birje. Efficient and Reliable Data Recovery Technique in Cloud Computing. Internet Things Cloud Comput. 2017, 5(5-1), 13-18. doi: 10.11648/j.iotcc.s.2017050501.13

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AMA Style

Praveen S. Challagidad, Ambika S. Dalawai, Mahantesh N. Birje. Efficient and Reliable Data Recovery Technique in Cloud Computing. Internet Things Cloud Comput. 2017;5(5-1):13-18. doi: 10.11648/j.iotcc.s.2017050501.13

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@article{10.11648/j.iotcc.s.2017050501.13,
  author = {Praveen S. Challagidad and Ambika S. Dalawai and Mahantesh N. Birje},
  title = {Efficient and Reliable Data Recovery Technique in Cloud Computing},
  journal = {Internet of Things and Cloud Computing},
  volume = {5},
  number = {5-1},
  pages = {13-18},
  doi = {10.11648/j.iotcc.s.2017050501.13},
  url = {https://doi.org/10.11648/j.iotcc.s.2017050501.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.iotcc.s.2017050501.13},
  abstract = {Cloud computing provides accessing of any kind of services dynamically over Internet on demand basis. One of the most significant service that is being provided is storage as a service. Cloud customer can store any amount of data into cloud storage results to huge amount of data at the datacenter. The data may get deleted by man-made disaster (either CSP or customer itself without their knowledge) or by natural disasters (either earth quakes or volcanoes) from the datacenters. Nowadays, data has been generated in large quantity that requires the data recovery services or techniques. Therefore there is a requirement for designing an efficient data recovery technique to recover the lost data. Many researchers have proposed different data recovery techniques but they lack in efficiency and reliability. In this paper, a multi-server system based on Enriched Genetic Algorithm to recover the lost data by using four cloud backup servers is discussed. To achieve reliability the proposed technique provides the flexibility for the user to collect information from any backup server when main cloud server loses its data and is unable to provide data to users.},
 year = {2017}
}

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TY - JOUR
T1 - Efficient and Reliable Data Recovery Technique in Cloud Computing
AU - Praveen S. Challagidad
AU - Ambika S. Dalawai
AU - Mahantesh N. Birje
Y1 - 2017/08/25
PY - 2017
N1 - https://doi.org/10.11648/j.iotcc.s.2017050501.13
DO - 10.11648/j.iotcc.s.2017050501.13
T2 - Internet of Things and Cloud Computing
JF - Internet of Things and Cloud Computing
JO - Internet of Things and Cloud Computing
SP - 13
EP - 18
PB - Science Publishing Group
SN - 2376-7731
UR - https://doi.org/10.11648/j.iotcc.s.2017050501.13
AB - Cloud computing provides accessing of any kind of services dynamically over Internet on demand basis. One of the most significant service that is being provided is storage as a service. Cloud customer can store any amount of data into cloud storage results to huge amount of data at the datacenter. The data may get deleted by man-made disaster (either CSP or customer itself without their knowledge) or by natural disasters (either earth quakes or volcanoes) from the datacenters. Nowadays, data has been generated in large quantity that requires the data recovery services or techniques. Therefore there is a requirement for designing an efficient data recovery technique to recover the lost data. Many researchers have proposed different data recovery techniques but they lack in efficiency and reliability. In this paper, a multi-server system based on Enriched Genetic Algorithm to recover the lost data by using four cloud backup servers is discussed. To achieve reliability the proposed technique provides the flexibility for the user to collect information from any backup server when main cloud server loses its data and is unable to provide data to users.
VL - 5
IS - 5-1
ER -

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Author Information

Praveen S. Challagidad

Department of Computer Science and Engineering, Basaveshwar Engineering College, Bagalkot, India
Ambika S. Dalawai

Department of Computer Science and Engineering, Basaveshwar Engineering College, Bagalkot, India
Mahantesh N. Birje

Center for Post Graduate Studies, Visvesvaraya Technological University (VTU), Belagavi, India

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Plain Text BibTeX RIS

APA Style

Praveen S. Challagidad, Ambika S. Dalawai, Mahantesh N. Birje. (2017). Efficient and Reliable Data Recovery Technique in Cloud Computing. Internet of Things and Cloud Computing, 5(5-1), 13-18. https://doi.org/10.11648/j.iotcc.s.2017050501.13

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ACS Style

Praveen S. Challagidad; Ambika S. Dalawai; Mahantesh N. Birje. Efficient and Reliable Data Recovery Technique in Cloud Computing. Internet Things Cloud Comput. 2017, 5(5-1), 13-18. doi: 10.11648/j.iotcc.s.2017050501.13

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AMA Style

Praveen S. Challagidad, Ambika S. Dalawai, Mahantesh N. Birje. Efficient and Reliable Data Recovery Technique in Cloud Computing. Internet Things Cloud Comput. 2017;5(5-1):13-18. doi: 10.11648/j.iotcc.s.2017050501.13

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@article{10.11648/j.iotcc.s.2017050501.13,
  author = {Praveen S. Challagidad and Ambika S. Dalawai and Mahantesh N. Birje},
  title = {Efficient and Reliable Data Recovery Technique in Cloud Computing},
  journal = {Internet of Things and Cloud Computing},
  volume = {5},
  number = {5-1},
  pages = {13-18},
  doi = {10.11648/j.iotcc.s.2017050501.13},
  url = {https://doi.org/10.11648/j.iotcc.s.2017050501.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.iotcc.s.2017050501.13},
  abstract = {Cloud computing provides accessing of any kind of services dynamically over Internet on demand basis. One of the most significant service that is being provided is storage as a service. Cloud customer can store any amount of data into cloud storage results to huge amount of data at the datacenter. The data may get deleted by man-made disaster (either CSP or customer itself without their knowledge) or by natural disasters (either earth quakes or volcanoes) from the datacenters. Nowadays, data has been generated in large quantity that requires the data recovery services or techniques. Therefore there is a requirement for designing an efficient data recovery technique to recover the lost data. Many researchers have proposed different data recovery techniques but they lack in efficiency and reliability. In this paper, a multi-server system based on Enriched Genetic Algorithm to recover the lost data by using four cloud backup servers is discussed. To achieve reliability the proposed technique provides the flexibility for the user to collect information from any backup server when main cloud server loses its data and is unable to provide data to users.},
 year = {2017}
}

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