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OGSO-DR: oppositional group search optimizer based efficient disaster recovery in a cloud environment

OGSO-DR: oppositional group search optimizer based efficient disaster recovery in a cloud... In cloud computing, enormous information storage is one of the great challenging tasks in term of reliable storage of sensitive data and quality of storage service. Among different cloud security issues, the data disaster recovery is the most critical issue. The motive of recovery technique is to help the user to collect data from any backup server when server lost his data and unable to provide data to the user. To achieve this purpose, many types of research develop different techniques. Therefore, in this paper, we propose a data disaster recovery process using Oppositional Group search optimizer (OGSO) algorithm which is mainly avoid the disaster in the cloud. The proposed data recovery process consists of four modules such as (1) file uploading module, (2) replica generation module, (3) data backup module and (4) disaster recovery module. At first, we split the data into a number of files and upload the file to the corresponding virtual machine using OGSO algorithm. After that, we generate the replica based on each file bandwidth. The replica is mainly used for data backup strategy. Finally, the user query based files are backup and retrieve based on replicas. The experimental results show that the proposed OGSO based data disaster recovery process is better than other approaches. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Ambient Intelligence and Humanized Computing Springer Journals

OGSO-DR: oppositional group search optimizer based efficient disaster recovery in a cloud environment

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References (31)

Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Engineering; Computational Intelligence; Artificial Intelligence; Robotics and Automation; User Interfaces and Human Computer Interaction
ISSN
1868-5137
eISSN
1868-5145
DOI
10.1007/s12652-018-0781-8
Publisher site
See Article on Publisher Site

Abstract

In cloud computing, enormous information storage is one of the great challenging tasks in term of reliable storage of sensitive data and quality of storage service. Among different cloud security issues, the data disaster recovery is the most critical issue. The motive of recovery technique is to help the user to collect data from any backup server when server lost his data and unable to provide data to the user. To achieve this purpose, many types of research develop different techniques. Therefore, in this paper, we propose a data disaster recovery process using Oppositional Group search optimizer (OGSO) algorithm which is mainly avoid the disaster in the cloud. The proposed data recovery process consists of four modules such as (1) file uploading module, (2) replica generation module, (3) data backup module and (4) disaster recovery module. At first, we split the data into a number of files and upload the file to the corresponding virtual machine using OGSO algorithm. After that, we generate the replica based on each file bandwidth. The replica is mainly used for data backup strategy. Finally, the user query based files are backup and retrieve based on replicas. The experimental results show that the proposed OGSO based data disaster recovery process is better than other approaches.

Journal

Journal of Ambient Intelligence and Humanized Computing – Springer Journals

Published: May 30, 2018

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