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Availability modeling and analysis of a disaster-recovery-as-a-service solution

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Abstract

In modern corporate environments, having a disaster recovery solution is no longer a luxury but a business necessity. The adoption of a disaster recovery solution, however, can be costly and often only affordable by large enterprises. Disaster-Recovery-as-a-Service (DRaaS) is a cloud-based solution that small and medium-sized businesses have been adopting to guarantee availability even in catastrophic situations. It offers lower acquisition and operational costs than traditional solutions. This work presents availability models for evaluating a DRaaS solution taking into account crucial disaster recovery metrics, such as downtime, costs, recovery time objective, and transaction loss. Furthermore, we performed sensitivity analysis on the DRaaS model to determine the parameters that cause the greatest impact on the system availability. Based on these analyses, disaster recovery coordinators can determine the optimum point to recover the damaged system by balancing the cost of system downtime against the cost of resources required for restoring the system. Our numerical results show the effectiveness of a DRaaS solution in terms of downtime, cost, and transition loss.

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Acknowledgements

The authors would like to thank FACEPE and CNPq for the financial support provided to this research.

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Authors and Affiliations

  1. Statistics and Informatics Department (DEINFO), Federal Rural University of Pernambuco, Recife, PE, Brazil

    Ermeson Andrade & Gustavo Callou

  2. Center of Informatics, Federal University of Pernambuco, Recife, PE, Brazil

    Rubens Matos & Paulo Maciel

  3. Academic Unit of Garanhuns (UAG), Federal Rural University of Pernambuco, Recife, PE, Brazil

    Bruno Nogueira

Authors
  1. Ermeson Andrade
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  2. Bruno Nogueira
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  3. Rubens Matos
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  4. Gustavo Callou
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  5. Paulo Maciel
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Correspondence to Ermeson Andrade.

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Andrade, E., Nogueira, B., Matos, R. et al. Availability modeling and analysis of a disaster-recovery-as-a-service solution. Computing 99, 929–954 (2017). https://doi.org/10.1007/s00607-017-0539-8

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  • DOI: https://doi.org/10.1007/s00607-017-0539-8

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