Improved feature selection and stream traffic classification based on machine learning in software-defined networks

• Main Authors: Arwa M. Eldhai, Mosab Hamdan, Ahmed Abdelaziz, Ibrahim Abaker Targio Hashem, Sharief F. Babiker, M. N. Marsono, Muzaffar Hamzah, Noor Zaman Jhanjhi
• Format: Article
• Language: English; English
• Published: IEEE 2024
• Subjects: QA75.5-76.95 Electronic computers. Computer science; TK7885-7895 Computer engineering. Computer hardware
• Online Access: https://eprints.ums.edu.my/id/eprint/41491/1/ABSTRACT.pdf; https://eprints.ums.edu.my/id/eprint/41491/2/FULL%20TEXT.pdf; https://eprints.ums.edu.my/id/eprint/41491/
• Institution: Universiti Malaysia Sabah

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...