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dc.contributor.authorBermbach, David*
dc.date.accessioned2021-02-11T08:56:23Z
dc.date.available2021-02-11T08:56:23Z
dc.date.issued2014*
dc.date.submitted2019-07-30 20:01:58*
dc.identifier34555*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/41940
dc.description.abstractCloud storage services and NoSQL systems typically offer only ""Eventual Consistency"", a rather weak guarantee covering a broad range of potential data consistency behavior. The degree of actual (in-)consistency, however, is unknown. This work presents novel solutions for determining the degree of (in-)consistency via simulation and benchmarking, as well as the necessary means to resolve inconsistencies leveraging this information.*
dc.languageEnglish*
dc.subjectHF5001-6182*
dc.subject.otherverteilte Systeme*
dc.subject.otherKonsistenz*
dc.subject.otherConsistency*
dc.subject.otherDistributed Database Management Systems*
dc.subject.otherEventual ConsistencyBenchmarking*
dc.subject.otherBenchmarking*
dc.subject.otherEventual Consistency*
dc.subject.otherDistributed Systems*
dc.subject.otherverteilte Datenbanken*
dc.titleBenchmarking Eventually Consistent Distributed Storage Systems*
dc.typebook
oapen.identifier.doi10.5445/KSP/1000039389*
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2*
oapen.relation.isbn9783731501862*
oapen.pagesVIII, 183 p.*


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