ML-based performance prediction of SDN using simulated data from real and synthetic networks

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Metadaten
Author:Katharina Dietz, Nicholas Gray, Michael SeufertORCiDGND, Tobias Hoßfeld
URN:urn:nbn:de:bvb:384-opus4-1072545
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/107254
ISBN:978-1-6654-0601-7OPAC
ISSN:2374-9709OPAC
Parent Title (English):NOMS 2022 - 2022 IEEE/IFIP Network Operations and Management Symposium, April 25-29, 2022, Budapest, Hungary
Publisher:IEEE
Place of publication:Piscataway, NJ
Editor:Pal Varga, Lisandro Zambenedetti Granville, Alex Galis, Istvan Godor, Noura Limam, Prosper Chemouil, Jérôme François, Marc-Oliver Pahl
Type:Conference Proceeding
Language:English
Year of first Publication:2022
Publishing Institution:Universität Augsburg
Release Date:2023/10/11
First Page:1
Last Page:7
DOI:https://doi.org/10.1109/noms54207.2022.9789916
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für vernetzte eingebettete Systeme und Kommunikationssysteme
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht