A Cloud-Based Adaptive Disaster Recovery Optimization Model
Omar Hussain Alhazmi · Computer and Information Science · 2016
Disaster recovery and business continuity plans are essential to make sure businesses keep on going. However, many small and medium businesses feel that these plans can cost them a lot. Moreover, the issues of cost and operation overhead prevent them from having solid disaster recovery plans. However, with the spread of cloud computing and pay-as-you-go and pay-for-what-you-use models, issues of operational overhead and expensive investment in extra storage and extra infrastructure are significantly minimized. On the other hand, as it becomes more affordable, businesses want to make sure they get the most optimal solution for minimum cost and overhead. In this work, we propose an adaptive cloud-based disaster recovery model that will be flexible in protecting data and applications with different plans by considering changes in risk levels and at the same time managing the costs and billing issues associated with the cloud. Therefore, this suggests an adaptive model to manage resources on the go while keeping costs as planned with the best possible protection.