DocumentCode
124494
Title
The distributed storage strategy research of remote sensing image based on Mongo DB
Author
Li Chaokui ; Yang Wu
Author_Institution
Nat.-Local Joint Eng. Lab. of Geo-spatial Inf. Technol., Hunan Univ. of Sci. & Technol., Xiangtan, China
fYear
2014
fDate
11-14 June 2014
Firstpage
101
Lastpage
104
Abstract
In recent years, with the wisdom of the city promote and research in the field of geographic space unceasingly thoroughly, the mass spatial data storage management and multiple concurrent access has become the research hotspot in the field of geosciences. Traditional spatial data storage is based on relational database, modeling, index mechanism, cache management and task scheduling method to realize the spatial data storage and scheduling. As a result of the limitation of performance, relational database already cannot satisfy the user´s high concurrency read/write performance and large scale spatial data organization and management. In this article, through debris type partition algorithm for the image division, put forward the non-relational database of remote sensing image data storage strategy based on the Mongo DB, on the premise of high concurrent access, without significant decline of read/write speed. Through experiment contrast the storage efficiency and multiple concurrent access efficiency with the remote sensing image storage method based on SQL Server database, the results show that the multiple concurrent access efficiency of the remote sensing image data storage based on Mongo DB is much better than the latter.
Keywords
geographic information systems; geophysics computing; relational databases; remote sensing; Mongo DB; cache management; distributed storage strategy research; geographic space field; geoscience field; image division; index mechanism; mass spatial data storage management; read-write speed; relational database; remote sensing image; remote sensing image data storage strategy; research hotspot; spatial data storage; task scheduling method; traditional spatial data storage; Databases; Earth; Image resolution; Joints; Maintenance engineering; Remote sensing; Servers; Debris typepartition algorithm; Mongo DB; NoSQL databases; RS image; SQL Server;
fLanguage
English
Publisher
ieee
Conference_Titel
Earth Observation and Remote Sensing Applications (EORSA), 2014 3rd International Workshop on
Conference_Location
Changsha
Print_ISBN
978-1-4799-5757-6
Type
conf
DOI
10.1109/EORSA.2014.6927858
Filename
6927858
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