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 …
sophisticated and dynamic. We develop a reinforcement learning routing algorithm …
Vulnerability assessment of 6G-enabled smart grid cyber–physical systems
Next-generation wireless communication and networking technologies, such as sixth-
generation (6G) networks and software-defined Internet of Things (SDIoT), make cyber …
generation (6G) networks and software-defined Internet of Things (SDIoT), make cyber …
SDN-enabled energy-efficient routing optimization framework for industrial Internet of Things
The traditional Internet architecture relies on the best-effort principle, which is not suitable for
critical industrial Internet of Things (IIoT) applications such as healthcare systems with …
critical industrial Internet of Things (IIoT) applications such as healthcare systems with …
A generative adversarial network enabled deep distributional reinforcement learning for transmission scheduling in internet of vehicles
The Cognitive Internet of Vehicles (CIoV) is an intelligent network that embeds the cognitive
mechanism in the Internet of Vehicles (IoV) to sense the environment and observe the …
mechanism in the Internet of Vehicles (IoV) to sense the environment and observe the …
[HTML][HTML] An adaptive network coding scheme for multipath transmission in cellular-based vehicular networks
With the emergence of vehicular Internet-of-Things (IoT) applications, it is a significant
challenge for vehicular IoT systems to obtain higher throughput in vehicle-to-cloud multipath …
challenge for vehicular IoT systems to obtain higher throughput in vehicle-to-cloud multipath …