P-CAGE: An Environment for Evolutionary Computation in Peer-to-Peer Systems

  • Gianluigi Folino
  • Giandomenico Spezzano
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3905)

Abstract

Solving complex real-world problems using evolutionary computation is a CPU time-consuming task that requires a large amount of computational resources. Peer-to-Peer (P2P) computing has recently revealed as a powerful way to harness these resources and efficiently deal with such problems. In this paper, we present a P2P implementation of Genetic Programming based on the JXTA technology. To run genetic programs we use a distributed environment based on a hybrid multi-island model that combines the island model with the cellular model. Each island adopts a cellular genetic programming model and the migration occurs among neighboring peers. The implementation is based on a virtual ring topology. Three different termination criteria (effort, time and max-gen) have been implemented. Experiments on some popular benchmarks show that the approach presents a accuracy at least comparable with classical distributed models, retaining the obvious advantages in terms of decentralization, fault tolerance and scalability of P2P systems.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Gianluigi Folino
    • 1
  • Giandomenico Spezzano
    • 1
  1. 1.Institute for High Performance Computing and Networking (ICAR)-CNRRende(CS)Italy

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