Maximizing Key Distribution Capability: An Application in Quantum Cryptography
Maximizing Key Distribution Capability: An Application in Quantum Cryptography
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DOI：
10.1109/qce57702.2023.00134
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发表时间：
2023-09
期刊：
影响因子：
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通讯作者：
Tu N. Nguyen;Dung H. P. Nguyen;Manh V. Nguyen;Thinh V. Le;Bing-Hong Liu;Thang N. Dinh
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文献类型：
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作者：
Tu N. Nguyen;Dung H. P. Nguyen;Manh V. Nguyen;Thinh V. Le;Bing-Hong Liu;Thang N. Dinh
量子密钥分布（QKD）集成波长划分多路复用（WDM）为钥匙交换问题提供了信息的安全解决方案。在本文中，我们调查了如何有效安排QKD以在WDM网络上提供足够的秘密键的联合问题。具体而言，我们首次采用混合整数线性编程（MILP）模型提出并提出最大化钥匙分布能力（MKDC）的问题。然后，我们建议采用两种用于解决多项式时间的较大尺度问题的近乎最佳算法。一种采用线性编程松弛技术与圆形算法（LPR-RA）结合使用，另一个是由以下事实启发的：较高的破坏风险的应用优先考虑秘密键，以补充秘密键，称为“渐进式服务算法”算法（PSA）。仿真结果表明，LPRRA和PSA都可以接近最佳的可行解决方案或问题的上限。另外，通过使用量子网络的开放模拟器NetSquid，我们进行了实验以了解BB84，这是当今QKD网络中普遍应用的协议。
Quantum key distribution (QKD) integrated wavelength-division multiplexing (WDM) offers an information-theoretically secure solution to the key exchange problem. In this paper, we investigate the joint problem of how to efficiently schedule QKD to provision sufficient secret keys over WDM networks. Specifically, we propose and formulate the problem of maximizing key distribution capability (MKDC) by employing a mixed integer linear programming (MILP) model for the first time. We then suggest two near-optimal algorithms adopted to address larger-scale problems in polynomial time. One employs the linear programming relaxation technique combined with a rounding algorithm (LPR-RA) and the other is inspired by the fact that the application with a higher risk of disruption is prioritized to recharge secret keys, dubbed progressive serving algorithm (PSA). Simulation results show that both the LPRRA and PSA can approach the best feasible solution or the upper-bound of the problem. In addition, by means of using NetSquid, an open simulator for quantum networks, we conduct experiments to get insight into the BB84, a protocol applied popularly in QKD networks nowadays.