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Machine-learning-based routing of QoS-constrained connectivity services in optical transport networks
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Optical Network Laboratory (ON Lab).
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Optical Network Laboratory (ON Lab).
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2018 (English)In: Optics InfoBase Conference Papers, Optical Society of America, 2018Conference paper, Published paper (Refereed)
Abstract [en]

Quality of Service (QoS) constraints are crucial in 5G networks. The paper presents a provisioning strategy for connectivity services with different priorities based on reinforcement learning able to accommodate QoS requirements while maximizing provider profits.

Place, publisher, year, edition, pages
Optical Society of America, 2018.
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-238406DOI: 10.1364/NETWORKS.2018.NeW3F.5Scopus ID: 2-s2.0-85051247443ISBN: 9781557528209 (print)OAI: oai:DiVA.org:kth-238406DiVA, id: diva2:1262496
Conference
Photonic Networks and Devices, Networks 2018, Zurich, Switzerland, 2 July 2018 through 5 July 2018
Note

QC 20181812

Available from: 2018-11-12 Created: 2018-11-12 Last updated: 2018-11-12Bibliographically approved

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Natalino, CarlosRaza, Muhammad RehanWosinska, LenaMonti, Paolo

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