A reinforcement learning approach for widest path routing in software-defined networks

A reinforcement learning approach for widest path routing in software-defined networks

In this paper, a routing method based on reinforcement learning (RL) under software-defined networks (SDN), namely the Q-learning widest-path routing algorithm (Q-WPRA), is proposed. This algorithm processes the reward function according to the link bandwidth in the execution environment to find the...

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Bibliographic Details
Main Authors: Chih-Heng Ke, Yi-Hao Tu, Yi-Wei Ma
Format: Article
Language:English
Published: Elsevier 2023-10-01
Series:ICT Express
Subjects:
Reinforcement learning
Software-defined networks
Reward function
Q-WPRA
Widest path
Online Access:http://www.sciencedirect.com/science/article/pii/S2405959522001503

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