Simplified resource provisioning for workflows in iaas clouds

Resource provisioning is an important and complicated problem for scientific workflows in Infrastructure-as-a-service (IaaS) clouds. Scientists are facing the complexities resulting from the diverse cloud offerings, complex workflow structures and characteristics as well as various user requirements on budget and performance. In this paper, we review the related work on the cost-aware optimizations of workflows in IaaS clouds and summarize the underlying research issues. Existing studies are not effective enough on finding good solutions to workflow optimization problems due to the complexity of workflows and the cloud dynamics. The heuristics proposed in the existing work are specifically designed for certain applications or certain budget and performance requirements. To address those issues, we propose a flexible and effective optimization system to simplify the resource provisioning for scientific workflows in IaaS clouds. The system adopts a probabilistic QoS notion to obtain good optimization results in the dynamic cloud environment and a cloud- and workflow-specific declarative language to specify various workflow optimization problems. We summarize our ongoing work and present some preliminary results on real-world scientific workflows. The experimental results demonstrate the effectiveness of our system on monetary cost optimizations and its capability to solve a wide class of optimization problems for scientific workflows.