Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/52878

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dc.contributor.authorCruz, Franciscopor
dc.contributor.authorMaia, Franciscopor
dc.contributor.authorMatos, Miguel Ângelo Marquespor
dc.contributor.authorOliveira, Rui Carlos Mendes depor
dc.contributor.authorPaulo, Joãopor
dc.contributor.authorPereira, Josépor
dc.contributor.authorVilaça, Ricardo Manuel Pereirapor
dc.date.accessioned2018-03-19T21:27:07Z-
dc.date.issued2016-
dc.identifier.isbn9783319395760-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/1822/52878-
dc.description.abstractIn order to attain the promises of the Cloud Computing paradigm, systems need to be able to transparently adapt to environment changes. Such behavior benefits from the ability to predict those changes in order to handle them seamlessly. In this paper, we present a mechanism to accurately predict the resource usage of distributed key-value datastores. Our mechanism requires offline training but, in contrast with other approaches, it is sufficient to run it only once per hardware configuration and subsequently use it for online prediction of database performance under any circumstance. The mechanism accurately estimates the database resource usage for any request distribution with an average accuracy of 94 %, only by knowing two parameters: (i) cache hit ratio; and (ii) incoming throughput. Both input values can be observed in real time or synthesized for request allocation decisions. This novel approach is sufficiently simple and generic, while simultaneously being suitable for other practical applications.por
dc.language.isoengpor
dc.publisherSpringer International Publishing AGpor
dc.rightsrestrictedAccesspor
dc.titleResource usage prediction in distributed key-value datastorespor
dc.typeconferencePaperpor
dc.peerreviewedyespor
oaire.citationStartPage144por
oaire.citationEndPage159por
oaire.citationVolume9687por
dc.date.updated2018-03-16T13:42:21Z-
dc.identifier.doi10.1007/978-3-319-39577-7_12por
dc.description.publicationversioninfo:eu-repo/semantics/publishedVersionpor
dc.subject.wosScience & Technology-
sdum.export.identifier4561-
sdum.journalLecture Notes in Computer Sciencepor
sdum.conferencePublicationDISTRIBUTED APPLICATIONS AND INTEROPERABLE SYSTEMS, DAIS 2016por
sdum.bookTitleDISTRIBUTED APPLICATIONS AND INTEROPERABLE SYSTEMS, DAIS 2016por
Appears in Collections:HASLab - Artigos em atas de conferências internacionais (texto completo)

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