Modeling Transcient Trace Data
| dc.contributor.author | Mathur, Anup | en |
| dc.contributor.author | Abrams, Marc | en |
| dc.contributor.department | Computer Science | en |
| dc.date.accessioned | 2013-06-19T14:35:56Z | en |
| dc.date.available | 2013-06-19T14:35:56Z | en |
| dc.date.issued | 1996-10-01 | en |
| dc.description.abstract | This 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 |
| dc.format.mimetype | application/postscript | en |
| dc.identifier | http://eprints.cs.vt.edu/archive/00000453/ | en |
| dc.identifier.sourceurl | http://eprints.cs.vt.edu/archive/00000453/01/TR-96-14.ps | en |
| dc.identifier.trnumber | TR-96-14 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/19941 | en |
| dc.language.iso | en | en |
| dc.publisher | Department of Computer Science, Virginia Polytechnic Institute & State University | en |
| dc.relation.ispartof | Historical Collection(Till Dec 2001) | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.title | Modeling Transcient Trace Data | en |
| dc.type | Technical report | en |
| dc.type.dcmitype | Text | en |
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