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

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Applications of Evolutionary Computation (EvoApplications 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10199))

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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.

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Notes

  1. 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.

References

  1. Ackley, D.H.: A Connectionist Machine for Genetic Hillclimbing. Kluwer Academic Publishers, Norwell (1987)

    Book  Google Scholar 

  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)

    Article  Google Scholar 

  3. Anetsberger, J., Bongard, J.: Robots can ground crowd-proposed symbols by forming theories of group mind. In: Proceedings Alife XV (2016)

    Google Scholar 

  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)

    Chapter  Google Scholar 

  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)

    Article  Google Scholar 

  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)

    Google Scholar 

  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_13

    Chapter  Google Scholar 

  8. Fajardo, E.M., Dost, J.M., Holzman, B., Tannenbaum, T., Letts, J., Tiradani, A., Bockelman, B., Frey, J., Mason, D.: How much higher can htcondor fly? J. Phys. Conf. Ser. 664(6), 062014 (2015). http://stacks.iop.org/1742-6596/664/i=6/a=062014

    Article  Google Scholar 

  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)

    Google Scholar 

  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)

    Google Scholar 

  11. Kosorukoff, A.: Human based genetic algorithm. In: 2001 IEEE International Conference on Systems, Man, and Cybernetics, vol. 5, pp. 3464–3469 (2001)

    Google Scholar 

  12. Langdon, W.B.: Pfeiffer - a distributed open-ended evolutionary system. In: Edmonds, B., Gilbert, N., Gustafson, S., Hales, D., Krasnogor, N. (eds.) AISB 2005: Proceedings of the Joint Symposium on Socially Inspired Computing (METAS 2005), 12–15 April 2005, pp. 7–13. University of Hertfordshire, Hatfield, UK (2005). http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/wbl_metas2005.pdf. sSAISB 2005 Convention

  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)

    Article  Google Scholar 

  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)

    Google Scholar 

  15. Martınez, G.J., Val, L.: Capataz: A framework for distributing algorithms via the World Wide Web. CLEI Electron. J. 18(2), 1 (2015)

    Article  Google Scholar 

  16. Masse, M.: REST API Design Rulebook. O’Reilly Media, Inc., Sebastopol (2011)

    Google Scholar 

  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)

    Google Scholar 

  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. Ornstein, D.S., Weiss, B.: Entropy and data compression schemes. IEEE Trans. Inf. Theory 39(1), 78–83 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  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)

    Google Scholar 

  21. Paulson, L.D.: Building rich web applications with ajax. Computer 38(10), 14–17 (2005)

    Article  Google Scholar 

  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/BFb0056943

    Chapter  Google Scholar 

  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)

    Google Scholar 

  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

    Google Scholar 

  25. Sarmenta, L.F.: Volunteer computing. Ph.D. thesis, Massachusetts Institute of Technology (2001)

    Google Scholar 

  26. Valdez, M.G., Trujillo, L., Merelo-Guervós, J.J., de Vega, F.F., Olague, G.: The evospace model for pool-based evolutionary algorithms. J. Grid Comput. 13(3), 329–349 (2015). http://dx.doi.org/10.1007/s10723-014-9319-2

    Article  Google Scholar 

  27. Vespignani, A., et al.: Predicting the behavior of techno-social systems. Science 325(5939), 425 (2009)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgments

This work has been supported in part by TIN2014-56494-C4-3-P (Spanish Ministry of Economy and Competitivity). We are also grateful to @otisdriftwood for his help gathering users for the new experiments.

Author information

Authors and Affiliations

  1. Department of Computer Architecture and Technology, University of Granada, Granada, Spain

    Juan J. Merelo & Paloma de las Cuevas

  2. CITIC, University of Granada, Granada, Spain

    Juan J. Merelo & Paloma de las Cuevas

  3. Department of Computer Engineering, University of Cádiz, Cádiz, Spain

    Pablo García-Sánchez

  4. Department of Graduate Studies, Instituto Tecnológico de Tijuana, Tijuana, Mexico

    Mario García-Valdez

Authors
  1. Juan J. Merelo
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  2. Paloma de las Cuevas
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  3. Pablo García-Sánchez
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  4. Mario García-Valdez
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Corresponding author

Correspondence to Juan J. Merelo .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Giovanni Squillero

  2. Edinburgh Napier University, Edinburgh, United Kingdom

    Kevin Sim

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Merelo, J.J., de las Cuevas, P., García-Sánchez, P., García-Valdez, M. (2017). A Performance Assessment of Evolutionary Algorithms in Volunteer Computing Environments: The Importance of Entropy. In: Squillero, G., Sim, K. (eds) Applications of Evolutionary Computation. EvoApplications 2017. Lecture Notes in Computer Science(), vol 10199. Springer, Cham. https://doi.org/10.1007/978-3-319-55849-3_52

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

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