A survey on machine learning techniques for routing optimization in SDN

R Amin, E Rojas, A Aqdus, S Ramzan… - IEEE …, 2021 - ieeexplore.ieee.org
In conventional networks, there was a tight bond between the control plane and the data
plane. The introduction of Software-Defined Networking (SDN) separated these planes, and …

DRSIR: A deep reinforcement learning approach for routing in software-defined networking

DM Casas-Velasco, OMC Rendon… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Traditional routing protocols employ limited information to make routing decisions, which
leads to slow adaptation to traffic variability and restricted support to the quality of service …

Intelligent routing based on reinforcement learning for software-defined networking

DM Casas-Velasco, OMC Rendon… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Traditional routing protocols employ limited information to make routing decisions, which
can lead to a slow adaptation to traffic variability, as well as restricted support to the Quality …

DROM: Optimizing the routing in software-defined networks with deep reinforcement learning

C Yu, J Lan, Z Guo, Y Hu - IEEE Access, 2018 - ieeexplore.ieee.org
This paper proposes DROM, a deep reinforcement learning mechanism for Software-
Defined Networks (SDN) to achieve a universal and customizable routing optimization …

A survey of machine learning techniques applied to software defined networking (SDN): Research issues and challenges

J Xie, FR Yu, T Huang, R Xie, J Liu… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
In recent years, with the rapid development of current Internet and mobile communication
technologies, the infrastructure, devices and resources in networking systems are becoming …

TIDE: Time-relevant deep reinforcement learning for routing optimization

P Sun, Y Hu, J Lan, L Tian, M Chen - Future Generation Computer Systems, 2019 - Elsevier
Routing optimization has been researched in network design for a long time, and plenty of
optimization schemes have been proposed from both academia and industry. However …

Improving the software-defined wireless sensor networks routing performance using reinforcement learning

MU Younus, MK Khan, AR Bhatti - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Software-defined networking (SDN) is an emerging architecture used in many applications
because of its flexible architecture. It is expected to become an essential enabler for the …

Deep reinforcement learning-based routing on software-defined networks

G Kim, Y Kim, H Lim - IEEE Access, 2022 - ieeexplore.ieee.org
With an exponential increase in network traffic demands requiring quality of services, the
need for routing optimization has become more prominent. Recently, the advent of software …

RL-routing: An SDN routing algorithm based on deep reinforcement learning

YR Chen, A Rezapour, WG Tzeng… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Communication networks are difficult to model and predict because they have become very
sophisticated and dynamic. We develop a reinforcement learning routing algorithm …

A survey of networking applications applying the software defined networking concept based on machine learning

Y Zhao, Y Li, X Zhang, G Geng, W Zhang, Y Sun - IEEE access, 2019 - ieeexplore.ieee.org
The main task of future networks is to build, as much as possible, intelligent networking
architectures for intellectualization, activation, and customization. Software-defined …