Show simple item record

dc.contributor.authorChristoforou, Evgeniaen
dc.contributor.authorFernández Anta, Antonioen
dc.contributor.authorGeorgiou, Chryssisen
dc.contributor.authorMosteiro, Miguel A.en
dc.contributor.authorSánchez, A.en
dc.creatorChristoforou, Evgeniaen
dc.creatorFernández Anta, Antonioen
dc.creatorGeorgiou, Chryssisen
dc.creatorMosteiro, Miguel A.en
dc.creatorSánchez, A.en
dc.date.accessioned2019-11-13T10:39:19Z
dc.date.available2019-11-13T10:39:19Z
dc.date.issued2013
dc.identifier.issn1532-0626
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/53738
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 processesen
dc.description.abstractworkers 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. Copyright © 2013 John Wiley & Sons, Ltd.en
dc.sourceConcurrency Computation Practice and Experienceen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84886641354&doi=10.1002%2fcpe.3104&partnerID=40&md5=f90069d3ea6c992a12de5e650e9a997d
dc.subjectInterneten
dc.subjectInternet baseden
dc.subjectAlgorithmsen
dc.subjectDynamicsen
dc.subjectMachine designen
dc.subjectComputer applicationsen
dc.subjectInternet based computingen
dc.subjectInternet-based computingen
dc.subjectalgorithmic mechanism designen
dc.subjectConvergence timeen
dc.subjectDynamics of evolutionen
dc.subjectevolutionary dynamicsen
dc.subjectMechanism-baseden
dc.subjectperforming tasksen
dc.subjectreinforcement learningen
dc.titleApplying the dynamics of evolution to achieve reliability in master-worker computingen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1002/cpe.3104
dc.description.volume25
dc.description.issue17
dc.description.startingpage2363
dc.description.endingpage2380
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeArticleen
dc.source.abbreviationConcurrency Comput.Pract.Exper.en
dc.contributor.orcidGeorgiou, Chryssis [0000-0003-4360-0260]
dc.contributor.orcidFernández Anta, Antonio [0000-0001-6501-2377]
dc.gnosis.orcid0000-0003-4360-0260
dc.gnosis.orcid0000-0001-6501-2377


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record