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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chen, Z. Yong Xue Jing Dong Jia Liu Yingjie Li |
| Copyright Year | 2012 |
| Description | Author affiliation: State Key Laboratory of Remote Sensing Science, jointly sponsored by the Institute of Remote Sensing Applications (IRSA) of the Chinese Academy of Sciences (CAS) and Beijing Normal University, IRSA, CAS, PO Box 9718, 100101, China (Jing Dong; Jia Liu; Yingjie Li) || Key Laboratory of Digital Earth, Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, No.9 Dengzhuang South Road, Haidian District, Beijing 100094, China (Chen, Z.; Yong Xue) |
| Abstract | The Remote Sensing Quantitative Retrieval is not only a Compute-intensive problem, but also a Data-intensive problem. One of the most effective solutions is Grid Computing platform built on the basis of network, which is a scalable virtual unified platform with unlimited computing power and storage capacity. The RSSN (Remote Sensing Information Service Grid Node) is a PC cluster for Remote Sensing Quantitative Retrieval. It was used for producing aerosol optical depth (AOD) production covered the land area of Asia. We designed the cluster as a hierarchical one, and achieved a Global Task Scheduler for the workflow process, improved the system performance to some extent. |
| Starting Page | 487 |
| Ending Page | 490 |
| File Size | 378272 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467311601 |
| ISSN | 21536996 |
| e-ISBN | 9781467311595 |
| e-ISBN | 9781467311588 |
| DOI | 10.1109/IGARSS.2012.6351380 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-07-22 |
| Publisher Place | Germany |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Remote sensing Computers Grid computing Earth Processor scheduling Educational institutions Aerosols five Remote Sensing Grid Computing three four |
| Content Type | Text |
| Resource Type | Article |
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