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

页码：487 / 490

页数：4

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