Abstract | ||
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Systems unavailability may produce severe consequences for modern business such as data loss, customer dissatisfaction, and subsequent revenue loss. Disaster recovery (DR) solutions have been adopted by many organizations as an attempt to prevent data loss and ensure business continuity. With the cloud computing expansion, different cloud providers have been offering low-cost solutions for DR purposes such as the Backup-as-a-service (BaaS) for consumers. Therefore, in this paper, we present an integrated model-experiment approach to evaluate a BaaS environment for DR purposes. We use analytic models and fault-injection experiments to evaluate DR keymetrics such as availability, downtime, Recovery Time Objective (RTO), and Recovery Point Objective (RPO) in a real-world BaaS environment. The results revealed that the environment availability can vary according to the amount of data to backed up and restored. Besides, a sensitivity analysis shows that the RTO and RPO are mainly influenced by the the mean time to recover from a disaster and the backup interval, respectively. |
Year | DOI | Venue |
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2019 | 10.1109/ISCC47284.2019.8969658 | 2019 IEEE Symposium on Computers and Communications (ISCC) |
Keywords | Field | DocType |
Disaster Recovery,Backup-as-a-Service,Faulttolerance,Petri nets | Data loss,Computer science,Computer network,Risk analysis (engineering),Unavailability,Recovery time objective,Business continuity,Downtime,Backup,Recovery point objective,Disaster recovery | Conference |
ISSN | ISBN | Citations |
1530-1346 | 978-1-7281-3000-2 | 0 |
PageRank | References | Authors |
0.34 | 8 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Júlio Mendonça | 1 | 1 | 1.38 |
Ricardo Lima | 2 | 51 | 6.91 |
Ewerton Queiroz | 3 | 0 | 0.34 |
Ermeson Andrade | 4 | 97 | 12.29 |
Dong Seong Kim | 5 | 866 | 93.34 |