1. Grid-enabled high-performance quantitative aerosol retrieval from remotely sensed data
- Author
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Xue, Yong, Ai, Jianwen, Wan, Wei, Guo, Huadong, Li, Yingjie, Wang, Ying, Guang, Jie, Mei, Linlu, and Xu, Hui
- Subjects
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AEROSOLS , *INFORMATION retrieval , *COUPLINGS (Gearing) , *REMOTE sensing , *GRID computing , *COMPUTER algorithms , *ELECTRONIC information resource searching , *CASE studies - Abstract
Abstract: As the quality and accuracy of remote-sensing instruments improve, the ability to quickly process remotely sensed data is in increasing demand. Quantitative remote-sensing retrieval is a complex computing process because of the terabytes or petabytes of data processed and the tight-coupling remote-sensing algorithms. In this paper, we intend to demonstrate the use of grid computing for quantitative remote-sensing retrieval applications with a workload estimation and task partition algorithm. Using a grid workflow for the quantitative remote-sensing retrieval service is an intuitive way to use the grid service for users without grid expertise. A case study showed that significant improvement in the system performance could be achieved with this implementation. The results of the case study also give a perspective on the potential of applying grid computing practices to remote-sensing problems. [ABSTRACT FROM AUTHOR]
- Published
- 2011
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