May 8, 2021 · The proposed scheme ScaleDRL employs the idea from the pinning control theory to select a subset of links in the network and name them critical ...
Sun et al. (2021) proposed a new scheme known as ScaleDRL based on deep reinforcement learning with SDN to design model-free traffic engineering using machine ...
Jan 11, 2024 · Our proposed scheme ScaleDRL employs the idea from the pinning control theory to select a subset of links in the network and name them critical ...
Dive into the research topics of 'ScaleDRL: A Scalable Deep Reinforcement Learning Approach for Traffic Engineering in SDN with Pinning Control'. Together they ...
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[Computer Network'21]ScaleDRL: A Scalable Deep Reinforcement Learning Approach for Traffic Engineering in SDN with Pinning Control 阅读笔记.
... reinforcement learning. J Netw Comp Appl 103116 ... ScaleDRL: a scalable deep reinforcement learning approach for traffic engineering in SDN with pinning control.
... engineering with reinforcement learning in SDN ... ScaleDRL: a scalable deep reinforcement learning approach for traffic engineering in SDN with pinning control.
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A deep reinforcement learning (DRL) framework coupled with the graph neural network (GNN) is proposed to realize CSPTP-based SC that adapts to changes of ...
CFR-RL algorithm is a reinforcement learning-based TE solution. It dynamically adjusts routes based on network state and traffic demand by autonomously learning ...