A Library to Run Evolutionary Algorithms in the Cloud Using MapReduce

  • Pedro Fazenda
  • James McDermott
  • Una-May O’Reilly
Conference paper

DOI: 10.1007/978-3-642-29178-4_42

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7248)
Cite this paper as:
Fazenda P., McDermott J., O’Reilly UM. (2012) A Library to Run Evolutionary Algorithms in the Cloud Using MapReduce. In: Di Chio C. et al. (eds) Applications of Evolutionary Computation. EvoApplications 2012. Lecture Notes in Computer Science, vol 7248. Springer, Berlin, Heidelberg

Abstract

We discuss ongoing development of an evolutionary algorithm library to run on the cloud. We relate how we have used the Hadoop open-source MapReduce distributed data processing framework to implement a single “island” with a potentially very large population. The design generalizes beyond the current, one-off kind of MapReduce implementations. It is in preparation for the library becoming a modeling or optimization service in a service oriented architecture or a development tool for designing new evolutionary algorithms.

Keywords

MapReduce cloud computing Hadoop evolutionary algorithms 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Pedro Fazenda
    • 1
    • 2
  • James McDermott
    • 2
  • Una-May O’Reilly
    • 2
  1. 1.Institute for Systems and RoboticsISTLisbonPortugal
  2. 2.Evolutionary Design and Optimization Group, CSAILMITUSA

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