QR-SDN: Towards Reinforcement Learning States, Actions, and Rewards for Direct Flow Routing in Software-Defined Networks

QR-SDN: Towards Reinforcement Learning States, Actions, and Rewards for Direct Flow Routing in Software-Defined Networks

Flow routing can achieve fine-grained network performance optimizations by routing distinct packet traffic flows over different network paths. While the centralized control of Software-Defined Networking (SDN) provides a control framework for implementing centralized network optimizations, e.g., opt...

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Bibliographic Details
Main Authors: Justus Rischke, Peter Sossalla, Hani Salah, Frank H. P. Fitzek, Martin Reisslein
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Flow routing
Q-table
software-defined networking (SDN)
state-space design
Online Access:https://ieeexplore.ieee.org/document/9201294/

Internet

https://ieeexplore.ieee.org/document/9201294/

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