A taxonomy of scientific workflow systems for grid computing
ACM SIGMOD Record
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
The UNICORE Rich Client: Facilitating the Automated Execution of Scientific Workflows
ESCIENCE '10 Proceedings of the 2010 IEEE Sixth International Conference on e-Science
The Aneka platform and QoS-driven resource provisioning for elastic applications on hybrid Clouds
Future Generation Computer Systems
An Evaluation of the Cost and Performance of Scientific Workflows on Amazon EC2
Journal of Grid Computing
WorkflowSim: A toolkit for simulating scientific workflows in distributed environments
E-SCIENCE '12 Proceedings of the 2012 IEEE 8th International Conference on E-Science (e-Science)
Hi-index | 0.00 |
Computational science workflows have been successfully run on traditional HPC systems like clusters and Grids for many years. Today, users are interested to execute their workflow applications in the Cloud to exploit the economic and technical benefits of this new emerging technology. The deployment and management of workflows over the current existing heterogeneous and not yet interoperable Cloud providers, however, is still a challenging task for the workflow developers. In this paper, we present a broker-based framework for running workflows in a multi-Cloud environment. The framework allows an automatic selection of the target Clouds, a uniform access to the Clouds, and workflow data management with respect to user Service Level Agreement (SLA) requirements. Following a simulation approach, we evaluated the framework with a real scientific workflow application in different deployment scenarios. The results show that our framework offers benefits to users by executing workflows with the expected performance and service quality at lowest cost.