ISSN: 0973-7510

E-ISSN: 2581-690X

S. Suguna1 and A. Suhasini2
1Department of Computer Science and Engineering, Annamalai University, Chidambaram- 608002, India.
2Department of Computer Science and Engineering, Annamalai University, Chidambaram- 608002, India.
J Pure Appl Microbiol. 2015;9(Spl. Edn. 1):653-664
© The Author(s). 2015
Received: 10/02/2015 | Accepted: 11/04/2015 | Published: 31/05/2015

Disaster occurrence may cause extensive misfortunes in the medical data base and a little amount of information loss leads to the mismatches in the health details within the medical database. So, it is necessary to pursue the disaster recovery and data protection technique to prevent data loss from the event of disaster. The disaster recovery procedure is identified with the continuation of technology infrastructure which is imperative to an medical data base in the cloud environment. The research of this paper proposed an EDRSA algorithm (Efficient Disaster Recovery Swist algorithm) for the process of automatic setting of Recovery Process Objective (RPO), Recovery Time Objective (RTO) and novel approach by utilizing the virtualization machine of Hybrid VMware VSphere. The virtual machines are booted from the virtual disk images that are stored in the cloud storage. The cloud framework has the capacity to run as one of the large file, even in the occurrence of any disaster. The RTO focused on the data retrieval time after a disaster has occurred and RPO set an objective point between the last backup and before the occurrence of disaster. This paper assessed the efficient improvement in Disaster Recovery by using an Swist algorithm for RTO and RPO under diverse conditions regarding metrics improvement and essential identification of disaster data in the healthcare cloud computing. Nonetheless, disaster losses of data can be reduced effectively to a maximum extent by establishing our proposed system model.


Disaster Recovery, virtual machine, Recovery Process Objective (RPO), Recovery Time Objective (RTO), healthcare cloud computing

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