Chapter

Applications of Evolutionary Computation

Volume 7248 of the series Lecture Notes in Computer Science pp 416-425

A Library to Run Evolutionary Algorithms in the Cloud Using MapReduce

  • Pedro FazendaAffiliated withUniversity of SurreyCornell UniversityInstitute for Systems and Robotics, ISTEvolutionary Design and Optimization Group, CSAIL, MIT
  • , James McDermottAffiliated withCornell UniversityEvolutionary Design and Optimization Group, CSAIL, MIT
  • , Una-May O’ReillyAffiliated withCornell UniversityEvolutionary Design and Optimization Group, CSAIL, MIT

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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