分布式空间分析运算关键技术

吴亮; 谢忠; 陈占龙; 马丽娜

doi:10.3799/dqkx.2010.040

Volume 35 Issue 3

May 2010

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Article Navigation > Earth Science > 2010 > 35(3): 362-368

WU Liang, XIE Zhong, CHEN Zhan-long, MA Li-na, 2010. Key Technology of Distributed Geospatial Information Operation. Earth Science, 35(3): 362-368. doi: 10.3799/dqkx.2010.040

Citation:

WU Liang, XIE Zhong, CHEN Zhan-long, MA Li-na, 2010. Key Technology of Distributed Geospatial Information Operation. Earth Science, 35(3): 362-368. doi: 10.3799/dqkx.2010.040

WU Liang, XIE Zhong, CHEN Zhan-long, MA Li-na, 2010. Key Technology of Distributed Geospatial Information Operation. Earth Science, 35(3): 362-368. doi: 10.3799/dqkx.2010.040

Citation:

WU Liang, XIE Zhong, CHEN Zhan-long, MA Li-na, 2010. Key Technology of Distributed Geospatial Information Operation. Earth Science, 35(3): 362-368. doi: 10.3799/dqkx.2010.040

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Key Technology of Distributed Geospatial Information Operation

doi: 10.3799/dqkx.2010.040

WU Liang^1
,,
XIE Zhong^{1
,
,},
CHEN Zhan-long^{1, 2},
MA Li-na^{1, 2}

1.
Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China
2.
Engineering Research Center of GIS Software and Applications, Ministry of Education, Wuhan 430074, China

Received Date: 2010-01-15
Publish Date: 2010-05-01

Abstract

Abstract

In order to improve spatial operation efficiency of massive data in distributed environment and to solve the interactive design problems of spatial analysis processing module designed to service agreement with the underlying database, spatial data models and so on. The basic characteristics of distributed computing are analyzed in this paper. The authors of this paper discuss the distributed computing spatial information technology system form the following aspects: apace computing task decomposition, distributed spatial data classification method, sharing data replication strategy, the data partitioning strategy based on the load and the caching mechanism of space computing framework. Based on this framework, the authors have developed the system for solving the practical problems, and solved the efficiency of large-scale spatial data operations in the complex distributed environment. At last, the distributed computing environment test of the classic space experiments has shown that, the framework is a design novelty, and can greatly reduce the spatial computing time in the distributed environments.
- distributed computing framework,
- spatial data partition,
- computing load balancing,
- geographic information system (GIS)

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References(24)

References

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