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dc.contributor.author Kolberg, Wagner
dc.contributor.author Marcos, Pedro de Botelho
dc.contributor.author Anjos, Julio Cesar Santos dos
dc.contributor.author Miyazaki, Alexandre Kenta Salgueiro
dc.contributor.author Geyer, Claudio Fernando Resin
dc.contributor.author Arantes, Luciana Bezerra
dc.date.accessioned 2015-06-01T01:06:17Z
dc.date.available 2015-06-01T01:06:17Z
dc.date.issued 2013
dc.identifier.citation KOLBERG, Wagner et al. MRSG – a MapReduce simulator over Simgrid. Parallel Computing, v. 39, n. 3-4, p. 233-244, 2013. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0167819113000215#>. Acesso em: 01 abr. 2015. pt_BR
dc.identifier.issn 0167-8191
dc.identifier.uri http://repositorio.furg.br/handle/1/4985
dc.description.abstract MapReduce is a parallel programming model to process large datasets, and it was inspired by the Map and Reduce primitives from functional languages. Its first implementation was designed to run on large clusters of homogeneous machines. Though, in the last years, the model was ported to different types of environments, such as desktop grid and volunteer computing. To obtain a good performance in these environments, however, it is necessary to adapt some framework mechanisms, such as scheduling and data distribution algorithms. In this paper we present the MRSG simulator, which reproduces the MapReduce work-flow on top of the SimGrid simulation toolkit, and provides an API to implement and evaluate these new algorithms and policies for MapReduce. To evaluate the simulator, we compared its behavior against a real Hadoop MapReduce deployment. The results show an important similarity between the simulated and real executions. pt_BR
dc.language.iso eng pt_BR
dc.rights restrict access pt_BR
dc.subject MapReduce pt_BR
dc.subject Data-intensive pt_BR
dc.subject Simulator pt_BR
dc.subject SimGrid pt_BR
dc.subject Simulator pt_BR
dc.title MRSG – a MapReduce simulator over SimGrid pt_BR
dc.type article pt_BR
dc.identifier.doi 10.1016/j.parco.2013.02.001 pt_BR


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