Model-Driven Application Refactoring to Minimize Deployment Costs in Preemptible Cloud Resources

Performance assessment of cloud-based applications requires new methodologies to deal with the complexity of software systems and the variability of cloud resources. In this paper, we address the problem of reducing the total costs for running cloud-based applications while fulfilling service-level...

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Bibliographic Details
Main Authors: Dubois, Daniel J., Trubiani, Catia, Casale, Giuliano
Format: Conference Proceeding
Language:English
Subjects:
application refactoring
Cloud computing
Computational modeling
Load modeling
Resource management
resource provisioning
Servers
software performance engineering
Unified modeling language
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Summary:Performance assessment of cloud-based applications requires new methodologies to deal with the complexity of software systems and the variability of cloud resources. In this paper, we address the problem of reducing the total costs for running cloud-based applications while fulfilling service-level objectives (SLOs). To this end, we define an approach to refactor a cloud application in such a way that, when it is deployed, it requires less computational capacity and therefore less resources. We experimented our approach on top of a modified optimal provisioning heuristic designed for preemptible cloud resources and the results show that it reduces deployment costs, up to 60% when compared to the same approach, but without model-driven application refactoring.
ISSN:2159-6190
DOI:10.1109/CLOUD.2016.0052