EvoSpace: a distributed evolutionary platform based on the tuple space model

Authors:
Mario García-Valdez;Leonardo Trujillo;Francisco Fernández de Vega;Juan J. Merelo Guervós;Gustavo Olague
Affiliations:
Instituto Tecnológico de Tijuana, Tijuana, BC, Mexico;Instituto Tecnológico de Tijuana, Tijuana, BC, Mexico;Grupo de Evolución Artificial, Universidad de Extremadura, Mérida, Spain;Universidad de Granada, Granada, Spain;Centro de Investigación Científica y de Educación Superior de Ensenada, Ensenada, BC, Mexico
Venue:
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
Year:
2013

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Abstract

This paper presents EvoSpace, a Cloud service for the development of distributed evolutionary algorithms. EvoSpace is based on the tuple space model, an associatively addressed memory space shared by several processes. Remote clients, called EvoWorkers, connect to EvoSpace and periodically take a subset of individuals from the global population, perform evolutionary operations on them, and return a set of new individuals. Several EvoWorkers carry out the evolutionary search in parallel and asynchronously, interacting with each other through the central repository. EvoSpace is designed to be domain independent and flexible, in the sense that in can be used with different types of evolutionary algorithms and applications. In this paper, a genetic algorithm is tested on the EvoSpace platform using a well-known benchmark problem, achieving promising results compared to a standard evolutionary system.