Jim Blythe, Ewa Deelman, and Yolanda Gil
Grid computing provides key infrastructure for distributed problem solving in dynamic virtual organizations. It has been adopted by many scientific projects, and industrial interest is rising rapidly. However, grids are still the domain of a few highly trained programmers with expertise in networking, high-performance computing, and operating systems. We have been working in capturing knowledge and heuristics about how to select application components and computing resources, and using that knowledge to generate automatically executable job workflows for a grid. Our system is implemented and integrated with a grid environment where it has generated dozens of workflows with hundreds of jobs in real time. In order to be applicable to a wide range of existing and new grid applications, the planner needs to be able to work with varying levels of semantic information for processes and the information they consume and create. We discuss our experiences dealing with different levels of data and describe a planning-based system that can provide different levels of support based in the information available.