Persistent Workflow on the Grid

The huge data requirements of large nowadays applications, in science, engineering, and commerce, make efficient data placement an essential need. For this purpose, we propose a framework which can be considered as a grid workflow system with advanced data placement capabilities. Computational jobs and data placement are handled concurrently. This framework also includes a specialised scheduling for data placement, and presents a multi-level architecture which allows support for a range of grid systems and middleware. We present results of improving application performance through data placement optimisations. A basic data mining application and an astronomy application are used as the basis of this study.