Evaluating and modelling solutions for disaster recovery. (1st August 2020)

• Record Type: Journal Article
• Authors: Mendonça, Júlio; Lima, Ricardo; Andrade, Ermeson
• Is Part Of: International journal of grid and utility computing. Volume 11:Number 5(2020)
• Page Start: 683
• Page End: 704
• Publication Date: 2020-08-01
• Subjects: backup-as-a-service -- cloud computing -- disaster recovery -- disaster tolerance -- fault-tolerance -- Petri nets -- stochastic modelling; Electronic data processing -- Distributed processing -- Periodicals; Electronic commerce -- Management -- Computer programs -- Periodicals; 004.605
• Languages: English
• ISSNs: 1741-847X

Abstract

Systems outages can have disastrous effects on businesses such as data loss, customer dissatisfaction, and subsequent revenue loss. Disaster recovery (DR) solutions have been adopted by companies to minimise the effects of these outages. However, the selection of an optimal DR solution is difficult since there does not exist a single solution that suits the requirement of every company (e.g., availability and costs). In this paper, we propose an integrated model-experiment approach to evaluate DR solutions. We perform experiments in different real-world DR solutions and propose analytic models to evaluate these solutions regarding DR key-metrics: steady-state availability, recovery time objective (RTO), recovery point objective (RPO), downtime, and costs. The results reveal that DR solutions can significantly improve availability and minimise costs. Also, a sensitivity analysis identifies the parameters that most affect the RPO and RTO of the DR adopted solutions.