Improved Feature Selection and Stream Traffic Classification Based on Machine Learning in Software-Defined Networks

Traffic classification (TC) in software-defined networks (SDN) using machine learning (ML) appears to be a viable option for improving network management. TC improves SDN operability, while SDN speeds up the feature selection (FS) process, especially when ML is used as a classification mechanism to...

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Autori principali:	Arwa M. Eldhai, Mosab Hamdan, Ahmed Abdelaziz, Ibrahim Abaker Targio Hashem, Sharief F. Babiker, M. N. Marsono, Muzaffar Hamzah, Noor Zaman Jhanjhi
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	IEEE 2024-01-01
Serie:	IEEE Access
Soggetti:	Adaptive random forest features selection Hoeffding adaptive trees k-nearest neighbor with adaptive sliding window detector machine learning software-defined networks
Accesso online:	https://ieeexplore.ieee.org/document/10445219/
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