Artificial Intelligence and Grids: Workflow Planning and Beyond January/February 2004 (vol. 19 no. 1) pp. 26-33
Grid computing is emerging as a key enabling infrastructure for science. A key challenge for distributed computation over the Grid is the on-demand synthesis of large-scale, end-to-end scientific applications that draw from pools of specialized scientific components to derive elaborate new results. Many technical issues must be addressed to meet this challenge, including usability, robustness, and scale. The Pegasus system generates executable grid workflows given highly specified desired results. Pegasus uses AI planning techniques to compose valid end-to-end workflows and has been used in several scientific applications.
Index Terms:
AI planning, workflow management, scientific workflows, AI applications, grid computing
Citation:
Yolanda Gil, Ewa Deelman, Jim Blythe, Carl Kesselman, Hongsuda Tangmunarunkit, "Artificial Intelligence and Grids: Workflow Planning and Beyond," IEEE Intelligent Systems, vol. 19, no. 1, pp. 26-33, Jan./Feb. 2004, doi:10.1109/MIS.2004.1265882 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||