• 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