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dc.contributor.authorGamarnik, David
dc.contributor.authorTsitsiklis, John N
dc.contributor.authorZubeldia, Martin
dc.date.accessioned2021-10-27T19:56:21Z
dc.date.available2021-10-27T19:56:21Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/1721.1/133724
dc.description.abstract© 2020 Institute of Mathematical Statistics. All rights reserved. We consider the following distributed service model: Jobs with unit mean, general distribution, and independent processing times arrive as a renewal process of rate λn, with 0 < λ < 1, and are immediately dispatched to one of several queues associated with n identical servers with unit processing rate. We assume that the dispatching decisions are made by a central dispatcher endowed with a finite memory, and with the ability to exchange messages with the servers. We study the fundamental resource requirements (memory bits and message exchange rate), in order to drive the expected queueing delay in steadystate of a typical job to zero, as n increases. We develop a novel approach to show that, within a certain broad class of "symmetric" policies, every dispatching policy with a message rate of the order of n, and with a memory of the order of log n bits, results in an expected queueing delay which is bounded away from zero, uniformly as n→∞. This complements existing results which show that, in the absence of such limitations on the memory or the message rate, there exist policies with vanishing queueing delay (at least with Poisson arrivals and exponential service times).
dc.language.isoen
dc.publisherInstitute of Mathematical Statistics
dc.relation.isversionof10.1214/19-AAP1519
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourcearXiv
dc.titleA lower bound on the queueing delay in resource constrained load balancing
dc.typeArticle
dc.contributor.departmentSloan School of Management
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.relation.journalAnnals of Applied Probability
dc.eprint.versionOriginal manuscript
dc.type.urihttp://purl.org/eprint/type/JournalArticle
eprint.statushttp://purl.org/eprint/status/NonPeerReviewed
dc.date.updated2021-04-01T14:18:27Z
dspace.orderedauthorsGamarnik, D; Tsitsiklis, JN; Zubeldia, M
dspace.date.submission2021-04-01T14:18:28Z
mit.journal.volume30
mit.journal.issue2
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Needed


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