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A key challenge for grid computing is creating large-scale, end-to-end scientific applications that draw from pools of specialized scientific components to derive elaborate new results. We develop Pegasus, an AI planning system which is integrated into the grid environment that takes a user's highly specified desired results, generates valid workflows that take into account available resources, and submits the workflows for execution on the grid. We also begin to extend it as a more distributed and knowledge-rich architecture.
Date of Publication: Jan-Feb 2004