• DocumentCode
    3601775
  • Title

    Multilayer Big Data Architecture for Remote Sensing in Eolic Parks

  • Author

    Moguel, Enrique ; Preciado, Juan C. ; Sanchez-Figueroa, Fernando ; Preciado, Miguel A. ; Hernandez, Juan

  • Author_Institution
    Dept. of Telematic & Informatic Syst. Eng., Univ. de Extremadura, Caceres, Spain
  • Volume
    8
  • Issue
    10
  • fYear
    2015
  • Firstpage
    4714
  • Lastpage
    4719
  • Abstract
    Due to their nature, Eolic parks are situated in zones with difficult access. As a result, management of Eolic parks using remote sensing techniques is of great importance. In addition, the huge amount of data managed by Eolic parks, together with their nature (distributed, heterogeneous, produced, consumed at different times, etc.) makes them ideal to apply big data techniques. In this paper, we present a multilayer hardware/software architecture that applies cloud computing techniques for managing big data from Eolic parks. This architecture allows tackling the processing of large, distributed, and heterogeneous data sets in a remote sensing context. An innovative contribution of this work is the combination of different techniques at three different layers of the proposed hardware/software architecture for Eolic park big data management and processing.
  • Keywords
    Big Data; cloud computing; geophysics computing; remote sensing; Eolic park big data management; Eolic park big data processing; big data technique; cloud computing technique; multilayer big data architecture; multilayer hardware architecture; multilayer software architecture; remote sensing; Big data; Cloud computing; Remote sensing; Substations; Wind turbines; Big data; Eolic parks; cloud computing; remote sensing; wind turbine;
  • fLanguage
    English
  • Journal_Title
    Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    1939-1404
  • Type

    jour

  • DOI
    10.1109/JSTARS.2015.2415583
  • Filename
    7080843