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Scalable Federated Learning over Passive Optical Networks
Chalmers University of Technology, Sweden.
RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems.ORCID iD: 0000-0001-9808-1483
Chalmers University of Technology, Sweden.
2021 (English)In: 2021 Optical Fiber Communications Conference and Exhibition, OFC 2021 - Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2021Conference paper, Published paper (Refereed)
Abstract [en]

Two-step aggregation is introduced to facilitate scalable federated learning (SFL) over passive optical networks (PONs). Results reveal that the SFL keeps the required PON upstream bandwidth constant regardless of the number of involved clients, while bringing 10% learning accuracy improvement. © 2021 OSA.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2021.
Keywords [en]
Optical fiber communication, Optical fibers, Passive networks, Learning accuracy, Passive optical networks
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:ri:diva-56128Scopus ID: 2-s2.0-85112089220ISBN: 9781943580866 (print)OAI: oai:DiVA.org:ri-56128DiVA, id: diva2:1590059
Conference
2021 Optical Fiber Communications Conference and Exhibition, OFC 2021, 6 June 2021 through 11 June 2021
Note

Funding details: Stiftelsen för Strategisk Forskning, SSF; Funding details: Vetenskapsrådet, VR, 2016-04489 FoundationforStrategicResearch; Funding text 1: Acknowledgment: This work is supported in part by Swedish Research Council (VR) project 2016-04489 FoundationforStrategicResearch(SSF),ChalmersICT-seedgrant, andhCalmersHCAIR-seedgrant.

Available from: 2021-09-01 Created: 2021-09-01 Last updated: 2023-05-25Bibliographically approved

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