Optimizing Time-Sensitive Software-Defined Wireless Networks With Reinforcement Learning

Optimizing Time-Sensitive Software-Defined Wireless Networks With Reinforcement Learning

Even though wireless networks are inevitable in mobile or infrastructure-less communication systems, such as vehicle-to-everything (V2X) infrastructure in automobile, precise formation control of unmanned vehicles (UVs), or other industries that employ ad hoc deployment of systems, operation and mai...

Full description

Saved in:
Bibliographic Details
Main Authors: Hyeontae Joo, Sangmin Lee, Seunghwan Lee, Hwangnam Kim
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Reinforcement learning
time-sensitive network
resource allocation
traffic control
Online Access:https://ieeexplore.ieee.org/document/9950062/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/9950062/

Similar Items