Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/MIS.2004.1265882 | IEEE Intelligent Systems |
Keywords | Field | DocType |
workflow planning,key enabling infrastructure,grid computing,ai planning technique,executable grid,artificial intelligence,key challenge,scientific application,pegasus system,specialized scientific component,end-to-end scientific application,valid end-to-end workflows,ai applications,artificial intelligent,workflow management,ai planning | Data science,Data mining,Grid computing,Software engineering,Computer science,Utility computing,Workflow engine,Workflow management system,Workflow,Grid,Automated planning and scheduling,Applications of artificial intelligence | Journal |
Volume | Issue | ISSN |
19 | 1 | 1541-1672 |
Citations | PageRank | References |
93 | 5.87 | 15 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yolanda Gil | 1 | 4491 | 413.53 |
| Ewa Deelman | 2 | 5948 | 420.48 |
| Jim Blythe | 3 | 707 | 73.61 |
| Carl Kesselman | 4 | 12860 | 1648.67 |
| Hongsuda Tangmunarunkit | 5 | 1043 | 189.72 |