Day 2, April 15 - Presentations
Title
MARS: Machine learning-based Adaptable and Robust network management for Software-defined networks
Start Date
15-4-2020 1:00 PM
End Date
15-4-2020 3:00 PM
Publisher
University of Tennessee at Chattanooga
Place of Publication
Chattanooga (Tenn.)
Abstract
MARS is an adaptable and robust network management approach using machine learning while considering the control plane architecture for software-defined networks. Project goal is enhancing the network resource utilization and SDN scalability.
Date
4-15-2020
Document Type
presentations
Language
English
Rights
http://rightsstatements.org/vocab/InC/1.0/
License
http://creativecommons.org/licenses/by-sa/4.0/
Recommended Citation
Ozcelik, Ilker; Kandah, Farah; and Huber, Brennan, "MARS: Machine learning-based Adaptable and Robust network management for Software-defined networks". ReSEARCH Dialogues Conference proceedings. https://scholar.utc.edu/research-dialogues/2020/day2_presentations/55.
MARS: Machine learning-based Adaptable and Robust network management for Software-defined networks
MARS is an adaptable and robust network management approach using machine learning while considering the control plane architecture for software-defined networks. Project goal is enhancing the network resource utilization and SDN scalability.