• DocumentCode
    262311
  • Title

    A Hadoop-Based Output Analyzer for Large-Scale Simulation Data

  • Author

    Kangsun Lee ; Joonho Park

  • Author_Institution
    Dept. of Comput. Eng., MyongJi Univ., Yongin, South Korea
  • fYear
    2014
  • fDate
    3-5 Dec. 2014
  • Firstpage
    197
  • Lastpage
    200
  • Abstract
    As modern simulations involve large inputs and outputs over the network, there is an increasing need to store, manage and analyze the massive datasets, efficiently. In this paper, we present ARLS (After action Reviewer for Large-Scale simulation data), a Hadoop-based output analysis tool for large-scale simulation datasets. ARLS clusters distributed storages using Hadoop and analyzes the large-scale datasets using MapReduce. According to the experiments we have conducted, ARLS improved data processing time significantly comparing to the traditional output analysis tools.
  • Keywords
    data handling; parallel processing; ARLS; Hadoop-based output analysis tool; Hadoop-based output analyzer; MapReduce; after action reviewer for large-scale simulation data; Analytical models; Atmospheric modeling; Cloud computing; Computational modeling; Computers; Data models; Educational institutions; Cloud Storages; Large-Scale Data Analysis; Modeling and Simulation for Large Scale Data; Output Analyzer;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on
  • Conference_Location
    Sydney, NSW
  • Type

    conf

  • DOI
    10.1109/BDCloud.2014.61
  • Filename
    7034786