research-article

Performance for the Masses: Experiments with A Web Based Architecture to Harness Volunteer Resources for Low Cost Distributed Evolutionary Computation

Authors:

Juan J. Merelo,

Pedro A. Castillo,

Pablo García-Sánchez,

Paloma de las Cuevas,

Mario García ValdezAuthors Info & Claims

GECCO '16: Proceedings of the Genetic and Evolutionary Computation Conference 2016

Pages 837 - 844

https://doi.org/10.1145/2908812.2908849

Published: 20 July 2016 Publication History

GECCO '16: Proceedings of the Genetic and Evolutionary Computation Conference 2016

Performance for the Masses: Experiments with A Web Based Architecture to Harness Volunteer Resources for Low Cost Distributed Evolutionary Computation

Pages 837 - 844

Abstract
References

Abstract

Using volunteer's browsers as a computing resource presents several advantages, but it remains a challenge to fully harness the browser's capabilities and to model the user's behavior so that those capabilities can be leveraged optimally. These are the objectives of this paper, where we present the results of several evolutionary computation experiments with different implementations of a volunteer computing framework called NodIO, designed to be easily deployable on freely available cloud resources. We use different implementations to find out which one is able to get the user to lend more computing cycles and test different problems to check the influence it has on said performance, as measured by the time needed to find a solution, but also by the number of users engaged. From these experiments we can already draw some conclusions, besides the fact that volunteer computing can be a valuable computing resource and that it is essential to be as open as possible with software and data: the user has to be kept engaged to obtain as many computing cycles as possible, the client has to be built to use the computer capabilities fully, and, finally, that the user contributions follow a common statistical distribution.

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Cited By

Felix-Saul JValdez MGuervós J(2022)A Novel Distributed Nature-Inspired Algorithm for Solving Optimization ProblemsNew Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics10.1007/978-3-031-08266-5_8(107-119)Online publication date: 1-Oct-2022
https://doi.org/10.1007/978-3-031-08266-5_8
García-Valdez MMerelo Guervós JLara LGarcía-Sánchez P(2018)Increasing Performance via Gamification in a Volunteer-Based Evolutionary Computation SystemInformation Processing and Management of Uncertainty in Knowledge-Based Systems. Applications10.1007/978-3-319-91479-4_29(342-353)Online publication date: 18-May-2018
https://doi.org/10.1007/978-3-319-91479-4_29
Garcia-Valdez MRomero JMancilla AGuervos J(2017)Exploiting the social graph: Increasing engagement in a collaborative Interactive Evolution application2017 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2017.7969385(749-756)Online publication date: Jun-2017
https://doi.org/10.1109/CEC.2017.7969385
Show More Cited By

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Performance for the Masses: Experiments with A Web Based Architecture to Harness Volunteer Resources for Low Cost Distributed Evolutionary Computation

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cover image ACM Conferences

GECCO '16: Proceedings of the Genetic and Evolutionary Computation Conference 2016

July 2016

1196 pages

ISBN:9781450342063

DOI:10.1145/2908812

Editor:
Tobias Friedrich
Hasso Plattner Institute
,
General Chair:
Frank Neumann
University of Adelaide
,
Program Chair:
Andrew M. Sutton
Hasso Plattner Institute

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 July 2016

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CONACYT
MECYT

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GECCO '16

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SIGEVO

GECCO '16: Genetic and Evolutionary Computation Conference

July 20 - 24, 2016

Colorado, Denver, USA

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GECCO '16 Paper Acceptance Rate 137 of 381 submissions, 36%;

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Felix-Saul JValdez MGuervós J(2022)A Novel Distributed Nature-Inspired Algorithm for Solving Optimization ProblemsNew Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics10.1007/978-3-031-08266-5_8(107-119)Online publication date: 1-Oct-2022
https://doi.org/10.1007/978-3-031-08266-5_8
García-Valdez MMerelo Guervós JLara LGarcía-Sánchez P(2018)Increasing Performance via Gamification in a Volunteer-Based Evolutionary Computation SystemInformation Processing and Management of Uncertainty in Knowledge-Based Systems. Applications10.1007/978-3-319-91479-4_29(342-353)Online publication date: 18-May-2018
https://doi.org/10.1007/978-3-319-91479-4_29
Garcia-Valdez MRomero JMancilla AGuervos J(2017)Exploiting the social graph: Increasing engagement in a collaborative Interactive Evolution application2017 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2017.7969385(749-756)Online publication date: Jun-2017
https://doi.org/10.1109/CEC.2017.7969385
Rivas VParras‐Gutiérrez EMerelo JArenas MGarcía‐Fernández P(2017)Time series forecasting using evolutionary neural nets implemented in a volunteer computing systemIntelligent Systems in Accounting, Finance and Management10.1002/isaf.140924:2-3(87-95)Online publication date: 8-Aug-2017
https://doi.org/10.1002/isaf.1409

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