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Optimal performance of parallel-server systems with job size prediction errors

dc.contributor.authorDoncel Vicente, Josu ORCID
dc.contributor.authorMancuso, Vincenzo
dc.date.accessioned2021-08-12T12:12:43Z
dc.date.available2021-08-12T12:12:43Z
dc.date.issued2021-05-12
dc.identifier.citationOperations Research Letters 49 : 459–464 (2021)es_ES
dc.identifier.issn0167-6377
dc.identifier.urihttp://hdl.handle.net/10810/52861
dc.description.abstract[EN] Modern communication networks integrate distributed computing architectures, in which customers are processed in parallel. We show how to minimize the waiting time of customer’s jobs by leveraging a simple threshold-based job dispatching policy. The optimal policy leverages the SITA routing, which assigns jobs to servers according to the size of the job. Moreover, the optimal policy permits to optimize system performance even when the job size is not known a priori and is estimated by means of error-prone predictors.es_ES
dc.description.sponsorshipThe work of Josu Doncel has been supported by the Department of Education of the Basque Government through the Consolidated Research Group MATHMODE (IT1294-19), by the Marie Sklodowska-Curie grant agreement No 777778 and by the Spanish Ministry of Science and Innovation with reference PID2019-108111RB-I00 (FEDER/AEI). The work of Vincenzo Mancuso has been supported by the Ramon y Cajal grant RYC-2014-16285 from the Spanish Ministry of Economy and Competitiveness, and by the Region of Madrid through the TAPIR-CM program (S2018/TCS-4496).es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/RYC-2014-16285es_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/PID2019-108111RB-I00es_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectparallel-server systemses_ES
dc.subjectsize-based routinges_ES
dc.subjectprediction errorses_ES
dc.titleOptimal performance of parallel-server systems with job size prediction errorses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2021 The Author(s). Published by Elsevier B.V. This article is available under the Creative Commons CC-BY-NC-ND license and permits non-commercial use of the work as published, without adaptation or alteration provided the work is fully attributed.es_ES
dc.rights.holderAtribución-NoComercial-SinDerivadas 3.0 España*
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0167637721000705es_ES
dc.identifier.doi10.1016/j.orl.2021.05.007
dc.departamentoesMatemáticases_ES
dc.departamentoeuMatematikaes_ES


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© 2021 The Author(s). Published by Elsevier B.V. This article is available under the Creative Commons CC-BY-NC-ND license and permits non-commercial use of the work as published, without adaptation or alteration provided the work is fully attributed.
Except where otherwise noted, this item's license is described as © 2021 The Author(s). Published by Elsevier B.V. This article is available under the Creative Commons CC-BY-NC-ND license and permits non-commercial use of the work as published, without adaptation or alteration provided the work is fully attributed.