Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Minimization of Systemic Risk for Directed Network Using Genetic Algorithm Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

A Performance Assessment of Evolutionary Algorithms in Volunteer Computing Environments: The Importance of Entropy

verfasst von : Juan J. Merelo, Paloma de las Cuevas, Pablo García-Sánchez, Mario García-Valdez

Erschienen in: Applications of Evolutionary Computation

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In a volunteer distributed computing system, users run a program on their own machine to contribute to a common effort. If the program is embedded in a web page, collaboration is straightforward, but also ephemeral. In this paper, we analyze a volunteer evolutionary computing system called NodIO, by running several experiments, some of them massive. Our objective is to discover rules that encourage volunteer participation and also the interplay of these contributions with the dynamics of the algorithm itself, making it more or less efficient. We will show different measures of participation and contribution to the algorithm, as well as how different volunteer usage patterns and tweaks in the algorithm, such as restarting clients when a solution has been found, contribute to improvements and leveraging of these contributions. We will also try to find out what is the key factor in the early termination of the experiments, measuring entropy in the contributions and other large scale indicators.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Embedded Grammars for Grammatical Evolution on GPGPU
Nächstes Kapitel Overcoming Initial Convergence in Multi-objective Evolution of Robot Control and Morphology Using a Two-Phase Approach
Fußnoten
1
It is not guaranteed to be running, or running the same version, when you read this, however; you can always get the sources from GitHub and set it up yourself.
 
Literatur
1.
Ackley, D.H.: A Connectionist Machine for Genetic Hillclimbing. Kluwer Academic Publishers, Norwell (1987)CrossRef
2.
Anderson, D.P., Cobb, J., Korpela, E., Lebofsky, M., Werthimer, D.: SETI@home: an experiment in public-resource computing. Commun. ACM 45(11), 56–61 (2002)CrossRef
3.
Anetsberger, J., Bongard, J.: Robots can ground crowd-proposed symbols by forming theories of group mind. In: Proceedings Alife XV (2016)
4.
Apolónia, N., Ferreira, P., Veiga, L.: Enhancing online communities with cycle-sharing for social networks. In: Abraham, A., Hassanien, A.-E. (eds.) Computational Social Networks, pp. 161–195. Springer, Heidelberg (2012)CrossRef
5.
Baumert, M., Baier, V., Haueisen, J., Wessel, N., Meyerfeldt, U., Schirdewan, A., Voss, A., et al.: Forecasting of life threatening arrhythmias using the compression entropy of heart rate. Methods Inf. Med. (Methodik der Information in der Medizin) 43(2), 202 (2004)CrossRef
6.
Boldrin, F., Taddia, C., Mazzini, G.: Distributed computing through web browser. In: 2007 IEEE 66th Vehicular Technology Conference, VTC-2007 Fall, pp. 2020–2024. IEEE (2007)
7.
Duda, J., Dłubacz, W.: Distributed evolutionary computing system based on web browsers with JavaScript. In: Manninen, P., Öster, P. (eds.) PARA 2012. LNCS, vol. 7782, pp. 183–191. Springer, Heidelberg (2013). doi:10.​1007/​978-3-642-36803-5_​13CrossRef
8.
9.
Gonzalez, D.L., de Vega, F.F., Trujillo, L., Olague, G., de la O, F.C., Cardenas, M., Araujo, L., Castillo, P.A., Sharman, K.: Increasing GP computing power via volunteer computing. CoRR abs/0801.1210 (2008)
10.
Klein, J., Spector, L.: Unwitting distributed genetic programming via asynchronous JavaScript and XML. In: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, GECCO 2007, pp. 1628–1635. ACM, New York (2007)
11.
Kosorukoff, A.: Human based genetic algorithm. In: 2001 IEEE International Conference on Systems, Man, and Cybernetics, vol. 5, pp. 3464–3469 (2001)
12.
13.
Laredo, J.L.J., Castillo, P.A., Mora, A.M., Merelo, J.J., Fernandes, C.: Resilience to churn of a peer-to-peer evolutionary algorithm. Int. J. High Perform. Syst. Architect. 1(4), 260–268 (2008)CrossRef
14.
Leclerc, G., Auerbach, J.E., Iacca, G., Floreano, D.: The seamless peer and cloud evolution framework. In: Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, pp. 821–828. ACM (2016)
15.
Martınez, G.J., Val, L.: Capataz: A framework for distributing algorithms via the World Wide Web. CLEI Electron. J. 18(2), 1 (2015)CrossRef
16.
Masse, M.: REST API Design Rulebook. O’Reilly Media, Inc., Sebastopol (2011)
17.
Merelo, J.J., García, A.M., Laredo, J.L.J., Lupión, J., Tricas, F.: Browser-based distributed evolutionary computation: performance and scaling behavior. In: Proceedings of the 2007 GECCO Conference Companion on Genetic and Evolutionary Computation, GECCO 2007, pp. 2851–2858. ACM, New York (2007)
18.
Merelo-Guervós, J.J., García-Sánchez, P.: Designing and modeling a browser-based distributed evolutionary computation system. In: Laredo, J.L.J., Silva, S., Esparcia-Alcázar, A.I. (eds.) Genetic and Evolutionary Computation Conference, GECCO 2015, Madrid, Spain, July 11–15, 2015, Companion Material Proceedings, pp. 1117–1124. ACM (2015). http://​doi.​acm.​org/​10.​1145/​2739482.​2768465
19.
20.
Pan, Y., White, J., Sun, Y., Gray, J.: Gray computing: an analysis of computing with background javascript tasks. In: Proceedings of the 37th International Conference on Software Engineering, vol. 1, pp. 167–177. IEEE Press (2015)
21.
Paulson, L.D.: Building rich web applications with ajax. Computer 38(10), 14–17 (2005)CrossRef
22.
Peñalver, J.G., Merelo, J.J.: Optimizing web page layout using an annealed genetic algorithm as client-side script. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, H.-P. (eds.) PPSN 1998. LNCS, vol. 1498, pp. 1018–1027. Springer, Heidelberg (1998). doi:10.​1007/​BFb0056943CrossRef
23.
Quinn, A.J., Bederson, B.B.: Human computation: a survey and taxonomy of a growing field. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1403–1412. ACM (2011)
24.
Rivas, V.M., Guervós, J.J.M., López, G.R., Arenas-García, M., Mora, A.M.: An object-oriented library in javascript to build modular and flexible cross-platform evolutionary algorithms. In: Esparcia-Alcázar, A.I., Mora, A.M. (eds.) EvoApplications 2014. LNCS, vol. 8602, pp. 853–862. Springer, Heidelberg (2014). doi:10.​1007/​978-3-662-45523-4_​69
25.
Sarmenta, L.F.: Volunteer computing. Ph.D. thesis, Massachusetts Institute of Technology (2001)
26.
27.
Metadaten
Titel
A Performance Assessment of Evolutionary Algorithms in Volunteer Computing Environments: The Importance of Entropy
verfasst von
Juan J. Merelo
Paloma de las Cuevas
Pablo García-Sánchez
Mario García-Valdez
Copyright-Jahr
2017
Buch
Applications of Evolutionary Computation

Print ISBN: 978-3-319-55848-6

Electronic ISBN: 978-3-319-55849-3

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-55849-3_52