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


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-05

AUTHORS

A. Arul Mary, K. Chitra

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. More... »

PAGES

1885-1895

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12652-018-0781-8

DOI

http://dx.doi.org/10.1007/s12652-018-0781-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1104302585


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