Volunteer computing in a scalable lightweight web-based environment

  • Pawel Chorazyk AGH University of Science and Technology
  • Aleksander Byrski AGH University of Science and Technology
  • Kamil Pietak AGH University of Science and Technology
  • Marek Kisiel-Dorohinicki AGH University of Science and Technology
  • Wojciech Turek AGH University of Science and Technology

Abstract

Volunteer computing is a very appealing way of utilizing vast available resources in efficient way. However, the current platforms that support such computing style are either difficult to use or not available at all, as a results of finished scientific projects, for example. In this paper, a novel lightweight volunteer computing platform is presented and thoroughly tested in an artificial environment of a commercially available computing cloud using two computing-related tasks and one web-crawling-related task.

Keywords

volunteer computing, distributed computing, metaheuristic computing, Javascript,

References

[1] BOINC. Detailed Statistics of all Projects. http://boincstats.com/en/stats/1/project/detail.
[2] BOINC User Manual: Android FAQ. http://boinc.berkeley.edu/wiki/Android FAQ.
[3] BOINC User Manual: GPU computing. http://boinc.berkeley.edu/wiki/GPU computing.
[4] Publications by BOINC projects. http://boinc.berkeley.edu/wiki/Publications by BOINC projects.
[5] World Community Grid Forums. Linux is here!!! 2005. http://www.worldcommunitygrid.org/forums/wcg/viewthread?thread=4224#33880.
[6] World Community Grid Forums: BOINC Migration Announcement, 2007. http://www.worldcommunitygrid.org/forums/wcg/viewthread?thread=15715.
[7] D.P. Anderson. BOINC: A system for public-resource computing and storage. In: 5th IEEE/ACM International Workshop on Grid Computing, pp. 4–10, 2004. https://boinc.berkeley.edu/grid paper 04.pdf.
[8] D.P. Anderson. Emulating volunteer computing scheduling policies. In: 2011 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum, 1839–1846, 2011.
[9] D.P. Anderson, J. Cobb, E. Korpela, M. Lebofsky, D.Werthimer. SETI@home: An experiment in public-resource computing. Communications of the ACM, 45(11): 56–61, 2002. http://setiathome.berkeley.edu/sah papers/cacm.php.
[10] D.P. Anderson, E. Korpela, R. Walton. High-performance task distribution for volunteer computing. In: Proceedings of the First International Conference on e-Science and Grid Computing, pp. 196–203. E-SCIENCE ’05, IEEE Computer Society, 2005. http://boinc.berkeley.edu/boinc papers/server perf/server perf.pdf.
[11] J.D. Baldassari. Design and Evaluation of a Public Resource Computing Framework. Master’s thesis, Worcester Polytechnic Institute, 2006. https://web.wpi.edu/Pubs/ETD/Available/etd-042006-225855/unrestricted/baldassari1.pdf.
[12] A.L. Beberg, D.L. Ensign, G. Jayachandran, S. Khaliq, V.S. Pande. Folding@home: Lessons from eight years of volunteer distributed computing. In: IEEE International Symposium on Parallel Distributed Processing, pp. 1–8, 2009. http://www.hicomb.org/HiCOMB2009/papers/HICOMB2009-13.pdf
[13] BME K¨ozigazgat´asi Informatikai K¨ozpont. GridBee Web Computing Framework – Official Website. http://webcomputing.iit.bme.hu/.
[14] M. Broniszewski, M. Poczwardowski, M. Zalewski. Comcute – Official Website. http://comcute.eti.pg.gda.pl/.
[15] A. Byrski, R. Dreżewski, L. Siwik, M. Kisiel-Dorohinicki. Evolutionary multi-agent systems. The Knowledge Engineering Review, 30(2): 171–186, 2015.
[16] P. Chorazyk, M. Godzik, K. Pietak, W. Turek, M. Kisiel-Dorohinicki, A. Byrski. Lightweight volunteer computing platform using web workers. Procedia Computer Science, 108: 948–957, 2017. Special Issue: International Conference on Computational Science, ICCS 2017, 12–14 June 2017, Zurich, Switzerland. http://www.sciencedirect.com/science/article/pii/S1877050917306348.
[17] D. Clery. IBM offers free number crunching for humanitarian research projects. Science, 308(5723): 773, 2005. http://andrewlawler.com/website/wpcontent/uploads/Science2005LawlerAstronomers Want to Be Heard Before NASA Acts775.pdf.
[18] P. Czarnul, J. Kuchta, M. Matuszek. Parallel computations in the volunteer – based Comcute system. In: Conference on Parallel Processing and Applied Mathematics, Lecture Notes in Computer Science, Springer, Berlin, Heidelberg, 8384: 261–271, 2014. https://www.researchgate.net/publication/260480164 Parallel Computations in the Volunteer based Comcute System.
[19] B. Czerwinski, R. Debski, K. Pietak. Distributed agent-based platform for large scale evolutionary computations. In: 2011 International Conference on Complex, Intelligent, and Software Intensive Systems, pp. 462–466, June 2011.
[20] R. Dębski, T. Krupa, P. Majewski. ComcuteJS: A web browser based platform for large-scale computations. Computer Science, 14(1): 2013. http://journals.agh.edu.pl/csci/article/view/113.
[21] distributed.net. distributed.net History and Timeline. http://www.distributed.net/History.
[22] distributed.net. Project RC5. http://www.distributed.net/RC5.
[23] distributed.net. RC5-56/Disposition of Prize Money. http://stats.distributed.net/misc/money.php?projectid=3.
[24] distributed.net. RC5-72/CPU Participation. http://stats.distributed.net/misc/platformlist.php?project id=8&view=tco.
[25] G. Fedak. Contributions to Desktop Grid Computing. Distributed, Parallel, and Cluster Computing [cs.DC]. Ecole Normale Sup´erieure de Lyon, 2015. https://hal.inria.fr/tel-01158462/file/hdr.pdf.
[26] G. Fedak, C. Cerin. Desktop Grid Computing. Chapman & Hall/CRC, 2012.
[27] J.E. Gallardo. C. Cotta, A.J. Fern´andez. Finding low autocorrelation binary sequences with memetic algorithms. Appl. Soft Comput., 9(4): 1252–1262, September 2009. http://www.lcc.uma.es/∼ccottap/papers/labsASC.pdf.
[28] IBM. IBM, United Devices and Accelrys Aid U.S. Department of Defense in Search for Smallpox Cure. IBM News releases, 2003. https://www-03.ibm.com/press/us/en/pressrelease/335.wss.
[29] IBM. IBM Introduces “World Community Grid”. IBM News releases, 2004. https://www-03.ibm.com/press/us/en/pressrelease/7404.wss.
[30] M. Kolybacz, M. Kowol, L. Lesniak, A. Byrski, M. Kisiel-Dorohinicki. Efficiency of memetic and evolutionary computing in combinatorial optimisation. In: European Council for Modeling and Simulation, ECMS, pp. 525–531, 2013.
[31] M. Kowol, K. Pietak, M. Kisiel-Dorohinicki, A. Byrski. Agent-based evolutionary and memetic black-box discrete optimization. Procedia Computer Science, 108: 907–916, 2017. Part of the International Conference on Computational Science, ICCS 2017, 12–14 June 2017, Zurich, Switzerland. http://www.sciencedirect.com/science/article/pii/S1877050917307573.
[32] T. MacWilliam, C. Cecka. CrowdCL: Web-based volunteer computing with WebCL. In: High Performance Extreme Computing Conference (HPEC), IEEE, pp. 1–6, September 2013. http://tommymacwilliam.com/docs/publications/hpec13.pdf.
[33] Mersenne Research, Inc. GIMPS history. http://www.mersenne.org/various/history.php.
[34] B.S. Naick, P.R. Kumar. Detection of low auto correlation binary sequences using meta heuristic approach. International Journal of Computer Applications, 106(10): 32–37, November 2014.
[35] Pande Lab, Stanford University. Folding@home: Papers. https://folding.stanford.edu/home/papers/.
[36] K. Pearson [Ed.]. Active Distributed Computing Projects. http://www.distributedcomputing.info/projects.html.
[37] K. Piętak, M. Kisiel-Dorohinicki. Agent-based framework facilitating component-based implementation of distributed computational intelligence systems. Transactions on Computational Collective Intelligence X, pp. 31–44. Part of the Lecture Notes in Computer Science book series (LNCS, volume 7776), Springer, Berlin, Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38496-7 3.
[38] L.F.G. Sarmenta. Bayanihan: Web-based volunteer computing using Java. In: Proceedings of the Second International Conference on Worldwide Computing and Its Applications, pp. 444–461, 1998. http://groups.csail.mit.edu/cag/bayanihan/papers/wwca98/html/.
[39] L.F.G. Sarmenta. Sabotage-tolerance mechanisms for volunteer computing systems. Future Generation Computer Systems, 18: 561–572, 2002. http://people.csail.mit.edu/lfgs/papers/ccgrid-fgcs.pdf.
[40] H. Schnell, A. Szarvas, G. Moln´ar, I. Szeber´enyi. GridBee web computing framework. In: The 7th BOINC Workshop, 2011. http://boinc.berkeley.edu/trac/raw-attachment/wiki/WorkShop11/GridBee.pdf.
[41] TOP500.org. Top500 List – November 2015. http://www.top500.org/list/2015/11/.
[42] University of California. Choosing BOINC projects. https://boinc.berkeley.edu/projects.php.
[43] University of California. SETI@home Classic: In Memoriam, 2005. http://setiathome.berkeley.edu/classic.php.
[44] Wikipedia. List of distributed computing projects. https://en.wikipedia.org/wiki/List of distributed computing projects.
[45] D. Żurek, K. Piętak, M. Pietroń, M. Kisiel-Dorohinicki. Toward hybrid platform for evolutionary computations of hard discrete problems. Procedia Computer Science, 108: 877–886, 2017. Part of the International Conference on Computational Science, ICCS 2017, 12–14 June 2017, Zurich, Switzerland. http://www.sciencedirect.com/science/article/pii/S1877050917307949.
Published
Sep 13, 2017
How to Cite
CHORAZYK, Pawel et al. Volunteer computing in a scalable lightweight web-based environment. Computer Assisted Methods in Engineering and Science, [S.l.], v. 24, n. 1, p. 17-40, sep. 2017. ISSN 2956-5839. Available at: <https://cames.ippt.gov.pl/index.php/cames/article/view/201>. Date accessed: 23 dec. 2024. doi: http://dx.doi.org/10.24423/cames.201.
Section
Articles