Name
Abstract | ||
|---|---|---|
A grid-computing platform facilitates geocomputational workflow composition to process big geosciences data while fully using idle resources to accelerate processing speed. An experiment with aerosol optical depth retrieval from satellite data shows a 25 percent improvement in runtime over a single high-performance computer. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/MC.2015.331 | IEEE Computer |
Keywords | Field | DocType |
Remote sensing,Data models,Processor scheduling,Geospatial analysis,Computational modeling,Aerosol optical depth,Grid computing | Geospatial analysis,Data modeling,Grid computing,Software engineering,Idle,Computer science,Real-time computing,Throughput,Workflow,Database,Grid,Satellite data | Journal |
Volume | Issue | ISSN |
48 | 11 | 0018-9162 |
Citations | PageRank | References |
1 | 0.43 | 13 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jia Liu | 1 | 10 | 5.97 |
| Yong Xue | 2 | 118 | 57.61 |
| Dominic Palmer-Brown. | 3 | 140 | 24.20 |
| Ziqiang Chen | 4 | 12 | 3.41 |
| Xingwei He | 5 | 2 | 2.55 |