Low or no cost distributed evolutionary computation
Pages 703 - 706
Abstract
From the era of big science we are back to the "do it yourself", where you do not have any money to buy clusters or subscribe to grids but still have algorithms that crave many computing nodes and need them to measure scalability. Fortunately, this coincides with the era of big data, cloud computing, and browsers that include JavaScript virtual machines. Those are the reasons why this talk will focus on two different aspects of volunteer or freeriding computing: first, the pragmatic: where to find those resources, which ones can be used, what kind of support you have to give them; and then, the theoretical: how evolutionary algorithms can be adapted to a environment in which nodes come and go, have different computing capabilities and operate in complete asynchrony of each other.
References
[1]
J. González, Juan-Julián Merelo-Guervós, P. A. Castillo, V. Rivas, G. Romero, and A. Prieto. Optimized web newspaper layout using simulated annealing. In José Mira and Juan Vincente Sánchez-Andrćs, editors, Engineering Applications of Bio-Inspired Artificial Neural Networks, International Work-Conference on Artificial and Natural Neural Networks, IWANN '99, Alicante, Spain, June 2--4, 1999, Proceedings, Volume II, volume 1607 of Lecture Notes in Computer Science, pages 759--768. Springer, 1999.
[2]
Juan-Luis Jiménez-Laredo, A. E. Eiben, Maarten van Steen, and Juan-Julián Merelo-Guervós. EvAg: a scalable peer-to-peer evolutionary algorithm. Genetic Programming and Evolvable Machines}, 11(2):227--246, 2010.
[3]
J. J. Merelo, P.A. Castillo, J.L.J. Laredo, A. Mora, and A. Prieto. Asynchronous distributed genetic algorithms with JavaScript and JSON. In WCCI 2008 Proceedings}, pages 1372--1379. IEEE Press, 2008.
[4]
Juan Julián Merelo Guervós. NodEO, a evolutionary algorithm library in Node. Technical report, GeNeura group, March 2014. Available at http://figshare.com/articles/nodeo/972892.
[5]
Juan Julián {Merelo-Guervós and Pablo Garcá-Sánchez. Modeling browser-based distributed evolutionary computation systems. ArXiv e-prints}, March 2015.
Index Terms
- Low or no cost distributed evolutionary computation
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Published: 11 July 2015
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