Using free cloud storage services for distributed evolutionary algorithms
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Characterizing fault-tolerance of genetic algorithms in desktop grid systems
EvoCOP'10 Proceedings of the 10th European conference on Evolutionary Computation in Combinatorial Optimization
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This paper presents how it is possible to increase the Genetic Programming (GP) Computing Power (CP) for free, via Volunteer Computing (VC), using the well known framework BOINC plus a new ``virtualization'' layer which adds all the benefits from the virtualization paradigm. Two different experiments, employing a standard GP tool and a complex GP system, are performed --with distributed PCs over several cities-- to show the free achieved CP by means of VC, without the necessity of modifying or adapting the original GP source code. The methodology can be easily extended to Evolutionary Algorithms (EAs).