ISSN : 1796-217X
Volume : 1    Issue : 2    Date : August 2006

A Jxta Based Asynchronous Peer-to-Peer Implementation of Genetic Programming
Gianluigi Folino, Agostino Forestiero, and Giandomenico Spezzano
Page(s): 12-23
Full Text:
PDF (749 KB)

Solving complex real-world problems using evolutionary computation is a CPU time-consuming
task that requires a large amount of computational resources. Peerto-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 P-CAGE: a P2P environment for Genetic Programming based
on the JXTA protocols. P-CAGE is based on a hybrid multi-island model that combines the island
model with the cellular model. Each island adopts a cellular model and the migration occurs
between neighboring peers placed in a virtual ring topology. Three different termination criteria
(effort, time and maxgen) have been implemented. Experiments were conducted on some popular
benchmarks and scalability, accuracy and the effect of migration have been studied. Performance
are at least comparable with classical distributed models, retaining the obvious advantages in
terms of decentralization, fault tolerance and scalability of P2P systems. We also demonstrated the
important effect of migration in accelerating the convergence.

Index Terms