Reinforcement Learning-based Resource Allocation in Quantum Key Distribution Networks

被引：0

作者：

Zuo, Yingmin ^{[1
]}

Zhao, Yongli ^{[1
]}

Yu, Xiaosong ^{[1
]}

Nag, Avishek ^{[2
]}

Zhang, Jie ^{[1
]}

机构：

[1] Beijing Univ Posts & Telecommun, State Key Lab Informat Photon & Opt Commun, Beijing 100876, Peoples R China

[2] Univ Coll Dublin, Sch Elect & Elect Engn, Dublin, Ireland

来源：

2020 ASIA COMMUNICATIONS AND PHOTONICS CONFERENCE (ACP) AND INTERNATIONAL CONFERENCE ON INFORMATION PHOTONICS AND OPTICAL COMMUNICATIONS (IPOC) | 2020年

基金：

中国国家自然科学基金;

关键词：

D O I：

暂无

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Efficient utilization of key resources is one of the key problems in quantum key distribution (QKD) networks. This paper verifies the effectiveness of using reinforcement learning to realize resource allocation in QKD networks. (C) 2020 The Author(s)

引用

页数：3

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