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Architecture-Level Software Performance Models for Online Performance Prediction

Brosig, Fabian Maria Konrad


Proactive performance and resource management of modern IT infrastructures requires the ability to predict at run-time, how the performance of running services would be affected if the workload or the system changes. In this thesis, modeling and prediction facilities that enable online performance prediction during system operation are presented. Analyses about the impact of reconfigurations and workload trends can be conducted on the model level, without executing expensive performance tests.

Volltext §
DOI: 10.5445/IR/1000043537
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Programmstrukturen und Datenorganisation (IPD)
Publikationstyp Hochschulschrift
Publikationsjahr 2014
Sprache Englisch
Identifikator urn:nbn:de:swb:90-435372
KITopen-ID: 1000043537
Verlag Karlsruher Institut für Technologie (KIT)
Art der Arbeit Dissertation
Fakultät Fakultät für Informatik (INFORMATIK)
Institut Institut für Programmstrukturen und Datenorganisation (IPD)
Prüfungsdaten 10.07.2014
Schlagwörter Software Performance Modeling, Software Performance Engineering, Software Performance Prediction
Referent/Betreuer Kounev, S.
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
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