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Applying the dynamics of evolution to achieve reliability in master-worker computing

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dc.affiliation.dptoUC3M. Departamento de Matemáticases
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Interdisciplinar de Sistemas Complejos (GISC)es
dc.contributor.authorChristoforou, Evgenia
dc.contributor.authorFernández Anta, Antonio
dc.contributor.authorGeorgiou, Chryssis
dc.contributor.authorMosteiro, Miguel A.
dc.contributor.authorSánchez, Angel
dc.date.accessioned2015-07-31T08:41:07Z
dc.date.available2015-07-31T08:41:07Z
dc.date.issued2013-08-01
dc.description.abstractWe consider Internet-based master-worker task computations, such as SETI@home, where a master process sends tasks, across the Internet, to worker processes; workers execute and report back some result. However, these workers are not trustworthy, and it might be at their best interest to report incorrect results. In such master-worker computations, the behavior and the best interest of the workers might change over time. We model such computations using evolutionary dynamics, and we study the conditions under which the master can reliably obtain task results. In particular, we develop and analyze an algorithmic mechanism based on reinforcement learning to provide workers with the necessary incentives to eventually become truthful. Our analysis identifies the conditions under which truthful behavior can be ensured and bounds the expected convergence time to that behavior. The analysis is complemented with illustrative simulations.en
dc.description.sponsorshipThis work is supported by the Cyprus Research Promotion Foundation grant TΠE/ΠΛHPO/0609(BE)/05, the National Science Foundation (CCF-0937829, CCF-1114930), Comunidad de Madrid grants S2009TIC-1692 and MODELICO-CM, Spanish PRODIEVO and RESINEE grants and MICINN grant EC2011-29688-C02-01, and National Natural Science Foundation of China grant 61020106002.en
dc.description.statusPublicado
dc.format.extent19
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationConcurrency and Computation: Practice and Experience 25 (2013) 17, pp.2363-2380es
dc.identifier.doi10.1002/cpe.3104
dc.identifier.issn1532-0626
dc.identifier.issn1532-0634 (Online)
dc.identifier.publicationfirstpage2363
dc.identifier.publicationissue17
dc.identifier.publicationlastpage2380
dc.identifier.publicationtitleConcurrency and computationen
dc.identifier.publicationvolume25
dc.identifier.urihttps://hdl.handle.net/10016/21481
dc.identifier.uxxiAR/0000014099
dc.language.isoeng
dc.publisherJohn Wiley & Sons, Ltd.en
dc.relation.projectIDGobierno de España. FIS2011-22449/PRODIEVOes
dc.relation.projectIDGobierno de España.TEC2011-29688-C02-01es
dc.relation.projectIDComunidad de Madrid. S2009/ESP-1691/MODELICOes
dc.relation.projectIDComunidad de Madrid. S2009TIC-1692es
dc.relation.publisherversionhttp://dx.doi.org/10.1002/cpe.3104
dc.rights© 2013 John Wiley & Sons, Ltd.en
dc.rights.accessRightsopen access
dc.subject.ecienciaMatemáticases
dc.subject.otherPerforming tasksen
dc.subject.otherInternet-based computingen
dc.subject.otherEvolutionary dynamicsen
dc.subject.otherReinforcement learningen
dc.subject.otherAlgorithmic mechanism designen
dc.titleApplying the dynamics of evolution to achieve reliability in master-worker computingen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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