Low-Latency Federated Reinforcement Learning-Based Resource Allocation in Converged Access Networks
conference contribution
posted on 2020-01-01, 00:00 authored by Lihua Ruan, Sourav Mondal, Imali DiasImali Dias, Elaine WongWe propose a federated reinforcement learning (FedRL) solution to innovate resource allocation in converged access networks. FedRL lowers network latency with reinforcement-learnt bandwidth decision and achieves fast learning with federated learning efforts.
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Volume
Part F174-OFC 2020Pagination
1-3Location
San Diego, CaliforniaPublisher DOI
Start date
2020-03-08End date
2020-03-12ISBN-13
9781943580712Language
engPublication classification
E1.1 Full written paper - refereedTitle of proceedings
OFC 2020 : Proceedings of the Optical Fiber Communication ConferenceEvent
Optical Fiber Communication. Conference (2020 : San Diego, California)Publisher
OSAPlace of publication
San Diego, Calif.Usage metrics
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