High-Throughput Geocomputational Workflows in a Grid Environment.

A grid-computing platform facilitates geocomputational workflow composition to process big geosciences data while fully using idle resources to accelerate processing speed. An experiment with aerosol optical depth retrieval from satellite data shows a 25 percent improvement in runtime over a single...

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Detalles Bibliográficos
Publicado en:Computer (00189162) Vol. 48; no. 11; pp. 70 - 81
Autores principales: Liu, Jia, Xue, Yong, Palmer-Brown, Dominic, Chen, Ziqiang, He, Xingwei
Formato: Artículo
Publicado: IEEE Nov2015
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        10.1109/MC.2015.331
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        atl: High-Throughput Geocomputational Workflows in a Grid Environment.
      aug:
        au:
          Liu, Jia
          Xue, Yong
          Palmer-Brown, Dominic
          Chen, Ziqiang
          He, Xingwei
        affil:
          Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences
          London Metropolitan University
      su:
        Workflow
        Grid computing
        Earth sciences
        Big data
        Aerosols
      sug:
        subj:
          Workflow
          Grid computing
          Earth sciences
          Big data
          Aerosols
      keyword:
        Aerosol optical depth
        Computational modeling
        Data models
        geocomputational workflow
        Geospatial analysis
        geospatial problems
        Processor scheduling
        quantitative retrieval
        Remote sensing
      ab: A grid-computing platform facilitates geocomputational workflow composition to process big geosciences data while fully using idle resources to accelerate processing speed. An experiment with aerosol optical depth retrieval from satellite data shows a 25 percent improvement in runtime over a single high-performance computer.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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