Zero touch management: A survey of network automation solutions for 5G and 6G networks

E Coronado, R Behravesh… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Mobile networks are facing an unprecedented demand for high-speed connectivity
originating from novel mobile applications and services and, in general, from the adoption …

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 …

Survey on multi-access edge computing for internet of things realization

P Porambage, J Okwuibe, M Liyanage… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
The Internet of Things (IoT) has recently advanced from an experimental technology to what
will become the backbone of future customer value for both product and service sector …

Deep reinforcement learning for cyber security

TT Nguyen, VJ Reddi - IEEE Transactions on Neural Networks …, 2021 - ieeexplore.ieee.org
The scale of Internet-connected systems has increased considerably, and these systems are
being exposed to cyberattacks more than ever. The complexity and dynamics of …

A comprehensive survey on machine learning for networking: evolution, applications and research opportunities

R Boutaba, MA Salahuddin, N Limam, S Ayoubi… - Journal of Internet …, 2018 - Springer
Abstract Machine Learning (ML) has been enjoying an unprecedented surge in applications
that solve problems and enable automation in diverse domains. Primarily, this is due to the …

Deep reinforcement learning: An overview

Y Li - arXiv preprint arXiv:1701.07274, 2017 - arxiv.org
We give an overview of recent exciting achievements of deep reinforcement learning (RL).
We discuss six core elements, six important mechanisms, and twelve applications. We start …

State-of-the-art deep learning: Evolving machine intelligence toward tomorrow's intelligent network traffic control systems

ZM Fadlullah, F Tang, B Mao, N Kato… - … Surveys & Tutorials, 2017 - ieeexplore.ieee.org
Currently, the network traffic control systems are mainly composed of the Internet core and
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …

RouteNet: Leveraging graph neural networks for network modeling and optimization in SDN

K Rusek, J Suárez-Varela, P Almasan… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
Network modeling is a key enabler to achieve efficient network operation in future self-
driving Software-Defined Networks. However, we still lack functional network models able to …

An exhaustive survey on p4 programmable data plane switches: Taxonomy, applications, challenges, and future trends

EF Kfoury, J Crichigno, E Bou-Harb - IEEE access, 2021 - ieeexplore.ieee.org
Traditionally, the data plane has been designed with fixed functions to forward packets using
a small set of protocols. This closed-design paradigm has limited the capability of the …

Deep reinforcement learning

SE Li - Reinforcement learning for sequential decision and …, 2023 - Springer
Similar to humans, RL agents use interactive learning to successfully obtain satisfactory
decision strategies. However, in many cases, it is desirable to learn directly from …