• DocumentCode
    652500
  • Title

    PER-MARE: Adaptive Deployment of MapReduce over Pervasive Grids

  • Author

    Steffenel, Luiz Angelo ; Flauzac, Olivier ; Schwertner Charao, Andrea ; Pitthan Barcelos, Patricia ; Stein, Bernardo ; Nesmachnow, Sergio ; Kirsch Pinheiro, Manuele ; Diaz, David

  • Author_Institution
    Univ. de Reims Champagne-Ardenne, Reims, France
  • fYear
    2013
  • fDate
    28-30 Oct. 2013
  • Firstpage
    17
  • Lastpage
    24
  • Abstract
    Map Reduce is a parallel programming paradigm successfully used to perform computations on massive amounts of data, being widely deployed on clusters, grid, and cloud infrastructures. Interestingly, while the emergence of cloud infrastructures has opened new perspectives, several enterprises hesitate to put sensible data on the cloud and prefer to rely on internal resources. In this paper we introduce the PER-MARE initiative, which aims at proposing scalable techniques to support existent Map Reduce data-intensive applications in the context of loosely coupled networks such as pervasive and desktop grids. By relying on the Map Reduce programming model, PER-MARE proposes to explore the potential advantages of using free unused resources available at enterprises as pervasive grids, alone or in a hybrid environment. This paper presents the main lines that orient the PER-MARE approach and some preliminary results.
  • Keywords
    grid computing; parallel programming; ubiquitous computing; MapReduce programming model; PER MARE initiative; adaptive deployment; cloud infrastructures; data intensive applications; desktop grids; hybrid environment; parallel programming paradigm; pervasive grids; sensible data; Computational modeling; Context; Fault tolerance; Fault tolerant systems; Peer-to-peer computing; Programming; Big data; MapReduce; pervasive cloud computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2013 Eighth International Conference on
  • Conference_Location
    Compiegne
  • Type

    conf

  • DOI
    10.1109/3PGCIC.2013.10
  • Filename
    6681204