PER-MARE: Adaptive Deployment of MapReduce over Pervasive Grids

Luiz Angelo Steffenel (1) , Olivier Flauzac (1) , Andrea Schwertner Charão (2) , Patricia Pitthan Barcelos (2) , Benhur Stein (2) , Sergio Nesmachnow (3) , Manuele Kirsch Pinheiro (4) , Daniel Diaz (4)

1 CRESTIC - Centre de Recherche en Sciences et Technologies de l'Information et de la Communication - EA 3804
2 LSC - Laboratório de Sistemas de Computação
3 UDELAR - UDELAR, Facultad de Ingenieria [Montevideo]
4 CRI - Centre de Recherche en Informatique de Paris 1

MapReduce 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 in- frastructures 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 MapReduce data-intensive applications in the context of loosely coupled networks such as pervasive and desktop grids. By relying on the MapReduce programming model, PER-MARE proposes to explore the potential advan- tages 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: Pervasive computing; MapReduce; Big data

Domains: Computer Science [cs]; Ubiquitous Computing; Computer Science [cs]; Distributed, Parallel, and Cluster Computing [cs.DC]

Luiz Angelo Steffenel, Olivier Flauzac, Andrea Schwertner Charão, Patricia Pitthan Barcelos, Benhur Stein, et al.. PER-MARE: Adaptive Deployment of MapReduce over Pervasive Grids. 8th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC'13), Oct 2013, COMPIEGNE, FRANCE, France. pp.17-24. ⟨hal-00903718⟩