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Reinforcement learn...
Reinforcement learning based multi-tenant secret-key assignment for quantum key distribution networks
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- Cao, Yuan (author)
- KTH,Skolan för elektroteknik och datavetenskap (EECS)
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Zhao, Y. (author)
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- Li, Jun (author)
- KTH,Skolan för elektroteknik och datavetenskap (EECS)
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- Lin, Rui (author)
- KTH,Optical Network Laboratory (ON Lab),Skolan för elektroteknik och datavetenskap (EECS)
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Zhang, J. (author)
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- Chen, Jiajia (author)
- KTH,Optical Network Laboratory (ON Lab),Skolan för elektroteknik och datavetenskap (EECS)
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(creator_code:org_t)
- Washington, D.C. OSA - The Optical Society, 2019
- 2019
- English.
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In: Optics InfoBase Conference Papers. - Washington, D.C. : OSA - The Optical Society.
- Related links:
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https://urn.kb.se/re...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
Close
- 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.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Telekommunikation (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Telecommunications (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
Keyword
- Blocking probability
- Optical fiber communication
- Optical fibers
- Probability distributions
- Reinforcement learning
- Multi tenants
- Secret key
- Quantum cryptography
Publication and Content Type
- ref (subject category)
- kon (subject category)
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