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dc.contributor.authorMathur, Anupen_US
dc.contributor.authorAbrams, Marcen_US
dc.date.accessioned2013-06-19T14:35:56Z
dc.date.available2013-06-19T14:35:56Z
dc.date.issued1996-10-01
dc.identifierhttp://eprints.cs.vt.edu/archive/00000453/en_US
dc.identifier.urihttp://hdl.handle.net/10919/19941
dc.description.abstractThis paper introduces a novel technique to construct an empirical workload model fitting time-varying (transient) trace data. The trace can be a categorical or numerical time-series. We model the trace as a Piecewise Independent stochastic process. To estimate the parameters for our model we first build a Rate Evolution Graph from the trace data. Piecewise linear regression is then used to construct a joint time-dependent probablity mass function for the trace data. Two methods are proposed to build a parsi- monious model. The modeling approach is demonstrated by the application of our model to twelve traces from the performance analysis domain.en_US
dc.format.mimetypeapplication/postscripten_US
dc.publisherDepartment of Computer Science, Virginia Polytechnic Institute & State Universityen_US
dc.relation.ispartofHistorical Collection(Till Dec 2001)en_US
dc.titleModeling Transcient Trace Dataen_US
dc.typeTechnical reporten_US
dc.identifier.trnumberTR-96-14en_US
dc.type.dcmitypeTexten_US
dc.identifier.sourceurlhttp://eprints.cs.vt.edu/archive/00000453/01/TR-96-14.ps


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