PER-MARE: Adaptive Deployment of MapReduce over Pervasive Grids
Luiz Angelo Steffenel, Olivier Flauzac, Andréa Schwertner Charão, Patrícia Pitthan Barcelos, Benhur de Oliveira Stein, Sergio Nesmachnow, Manuele Kirsch Pinheiro, Daniel Díaz · 2013 Eighth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing · 2013
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.