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Distributed media indexing based on MPI and MapReduce

Mohamed, Hisham ; Marchand-Maillet, Stéphane

In: Multimedia Tools and Applications, 2014, vol. 69, no. 2, p. 513-537

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    Titre
    • Distributed media indexing based on MPI and MapReduce
    Auteur
    • Mohamed, Hisham. Viper Group, Computer Vision and Multimedia Laboratory, University of Geneva, 7 Route de Drize, Geneva, Switzerland
    • Marchand-Maillet, Stéphane. Viper Group, Computer Vision and Multimedia Laboratory, University of Geneva, 7 Route de Drize, Geneva, Switzerland
    Type de document
    • Postprint
    Langue
    • Anglais
    Publié dans
    • Multimedia Tools and Applications, 2014, vol. 69, no. 2, p. 513-537. Springer US; http://www.springer-ny.com
    Autre version électronique
    Identifiant OAI-PMH
    • oai:doc.rero.ch:325233
    Summary
    Web-scale digital assets comprise millions or billions of documents. Due to such increase, sequential algorithms cannot cope with this data, and parallel and distributed computing become the solution of choice. MapReduce is a programming model proposed by Google for scalable data processing. MapReduce is mainly applicable for data intensive algorithms. In contrast, the message passing interface (MPI) is suitable for high performance algorithms. This paper proposes an adapted structure of the MapReduce programming model using MPI for multimedia indexing. Experimental results are done on various multimedia applications to validate our model. The experiments indicate that our proposed model achieves good speedup compared to the original sequential versions, Hadoop and the earlier versions of MapReduce using MPI.