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Reinforcement Learning Based Multi-Tenant Secret-Key Assignment for Quantum Key Distribution Networks
KTH, School of Electrical Engineering and Computer Science (EECS).
KTH, School of Electrical Engineering and Computer Science (EECS).
KTH, School of Electrical Engineering and Computer Science (EECS).
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2019 (English)In: 2019 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXHIBITION (OFC), IEEE, 2019Conference paper, Published paper (Refereed)
Abstract [en]

We propose a reinforcement learning based online multi-tenant secret-key assignment algorithm for quantum key distribution networks, capable of reducing tenant-request blocking probability more than half compared to the benchmark heuristics.

Place, publisher, year, edition, pages
IEEE, 2019.
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-268661ISI: 000469837300401ISBN: 978-1-9435-8053-8 (print)OAI: oai:DiVA.org:kth-268661DiVA, id: diva2:1394798
Conference
Optical Fiber Communications Conference and Exhibition (OFC), San Diego, CA, MAR 03-07, 2019
Note

QC 20200220

Available from: 2020-02-20 Created: 2020-02-20 Last updated: 2020-02-20Bibliographically approved

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CiteExportLink to record
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Citation style
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  • ieee
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