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Improving The Scalability Of Deep Reinforcement Learning-Based Routing With Control On Partial Nodes

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IEEE ICASSP 2020 Virtual Conference May 2020

Machine Learning (ML)-based routing optimization has been proposed to optimize the performance of flow routing for future networks, such as Software-Defined Networks (SDNs). However, existing studies are either hard to converge for large networks or vulne

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Improving The Scalability Of Deep Reinforcement Learning-Based Routing With Control On Partial Nodes

00:14:26

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Machine Learning (ML)-based routing optimization has been proposed to optimize the performance of flow routing for future networks, such as Software-Defined Networks (SDNs). However, existing studies are either hard to converge for large networks or vulne

Improving The Scalability Of Deep Reinforcement Learning-Based Routing With Control On Partial Nodes

00:00:00

0 views

Machine Learning (ML)-based routing optimization has been proposed to optimize the performance of flow routing for future networks, such as Software-Defined Networks (SDNs). However, existing studies are either hard to converge for large networks or vulne