SLA enactment for large-scale healthcare workflows on multi-Cloud

• An ontological model to semantically describe composite multi-Cloud services.
• A mathematical formulation of the SLA-based match-making problem on multi-Cloud.
• A utility-based genetic algorithm to optimize the selection of Cloud resources.
• A simulation-based evaluation with a real DNA sequencing healthcare workflow.
• The proposed matching algorithm reduces execution costs while fulfilling the SLAs.

Computing Clouds offer a new way of using IT facilities including the hardware, storage, applications and networks. The huge resource pool on the Cloud forms an appropriate platform for running applications with both computing and data intensity, like the DNA sequencing workflows. This paper studies the topic of running scientific workflows on multiple Clouds, with the DNA sequencing workflow as a driven application. We focus on the problem of matching the workflow functional and non-functional Service Level Agreement (SLA) requirements to the compute and storage services provisioned by underlying Clouds with different service price and quality. We designed an ontological model for a semantic description of the problem and developed a novel utility-based genetic matching algorithm for selecting the Cloud services with respect to the user requirements and the properties of the Clouds. We validated the approach by comparing the performance of the proposed algorithm with other matching algorithms in executing the DNA sequencing application on a realistic simulation platform. The results show the effectiveness of our approach in reducing the total costs and fulfilling the requested service quality even with large-scale service compositions.