• DocumentCode
    643649
  • Title

    Cloud storage of massive remote sensing data based on distributed file system

  • Author

    Ziwen Chi ; Feng Zhang ; Zhenhong Du ; Renyi Liu

  • Author_Institution
    Dept. of Geographic Inf. Sci., Zhejiang Univ. Hangzhou, Hangzhou, China
  • fYear
    2013
  • fDate
    5-8 Aug. 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Cloud storage is an effective means to solve the storage and management challenges of the growing mass remote sensing data products. In order to settle the problems existing in the application of cloud storage for remote sensing data, a distributed storage module based on image blocks organization was put forward, and the inefficient problem of distributed file system in massive image blocks storage was solved. In the combination of the module and HDFS, the efficient distributed storage and retrieval of image data were implemented, and the ability of spatial data access of the remote sensing data cloud storage was enabled. As built upon distributed file system, the storage system has a good scalability to meet the requirements of data growing. The experiment and analysis showed that the storage system could maintain a high throughput and stability under multiple concurrent connections.
  • Keywords
    cloud computing; distributed databases; geographic information systems; image retrieval; remote sensing; storage management; HDFS; Hadoop distributed file system; distributed storage module; image blocks organization; image data distributed storage; image data retrieval; massive image blocks storage; massive remote sensing data products; multiple concurrent connections; remote sensing data cloud storage; scalability; spatial data access; Cloud computing; Distributed databases; File systems; Image storage; Remote sensing; Scalability; Throughput; Cloud Storage; Distributed File System; Image Block Encoding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, Communication and Computing (ICSPCC), 2013 IEEE International Conference on
  • Conference_Location
    KunMing
  • Type

    conf

  • DOI
    10.1109/ICSPCC.2013.6663922
  • Filename
    6663922