THE TASK SCHEDULING FOR REMOTE SENSING QUANTITATIVE RETRIEVAL BASED ON HIERARCHICAL GRID COMPUTING PLATFORM

被引：2
|
作者：
Chen, Ziqiang [1 ,4 ]
Xue, Yong [1 ,2 ]
Dong, Jing [3 ,4 ]
Liu, Jia [3 ,4 ]
Li, Yingjie [4 ]
机构：
[1] Chinese Acad Sci, Key Lab Digital Earth, Ctr Earth Observat & Digital Earth, 9 Dengzhuang S Rd, Beijing 100094, Peoples R China
[2] London Metropolitan Univ, Fac Comp, London N7 8DB, England
[3] Chinese Acad Sci CAS & Beijing Normal Univ, Jointly Sponsored Inst Remote Sensing Applicat IR, State Key Lab Remote Sensing Sci, IRSA, Beijing 100101, Peoples R China
[4] Grad Univ, Chinese Acad Sci, Beijing, Peoples R China
来源：
2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2012年
基金：
中国国家自然科学基金;
关键词：
Remote Sensing; Grid Computing; three; four; five;
D O I：
10.1109/IGARSS.2012.6351380
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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.
引用
收藏
页码：487 / 490
页数：4
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