基于 DRL 的量子密钥分发网络渐进恢复技术

IF 4 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Mengyao Li;Qiaolun Zhang;Alberto Gatto;Stefano Bregni;Giacomo Verticale;Massimo Tornatore
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引用次数: 0

摘要

通过渐进式网络恢复,运营商可在大规模故障后通过多个阶段恢复网络连接,方法是确定最佳修复行动顺序,以最大限度地提高所承载的实时流量。在这项工作中,我们对 QKD 网络中的渐进式 QKD 网络恢复(PQNR)问题进行了建模和求解,以加快故障后的恢复速度。我们制定了一个整数线性规划(ILP)模型,以优化四种不同 QKD 网络架构在恢复期间可实现的累积密钥率,同时考虑到使用可信中继和光旁路的不同能力。由于 ILP 模型的计算局限性,我们提出了一种基于双延迟深度确定性策略梯度(TD3)框架的深度强化学习(DRL)算法,以解决大规模拓扑的 PQNR 问题。仿真结果表明,与最优解相比,我们提出的算法接近度很高,性能优于几种基准算法。此外,与仅使用光旁路和仅使用可信中继的情况相比,联合使用光旁路和可信中继可将密钥率性能分别提高 14% 和 18%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DRL-based progressive recovery for quantum-key-distribution networks
With progressive network recovery, operators restore network connectivity after massive failures along multiple stages, by identifying the optimal sequence of repair actions to maximize carried live traffic. Motivated by the initial deployments of quantum-key-distribution (QKD) over optical networks appearing in several locations worldwide, in this work we model and solve the progressive QKD network recovery (PQNR) problem in QKD networks to accelerate the recovery after failures. We formulate an integer linear programming (ILP) model to optimize the achievable accumulative key rates during recovery for four different QKD network architectures, considering different capabilities of using trusted relay and optical bypass. Due to the computational limitations of the ILP model, we propose a deep reinforcement learning (DRL) algorithm based on a twin delayed deep deterministic policy gradients (TD3) framework to solve the PQNR problem for large-scale topologies. Simulation results show that our proposed algorithm approaches well compared to the optimal solution and outperforms several baseline algorithms. Moreover, using optical bypass jointly with trusted relay can improve the performance in terms of the key rate by 14% and 18% compared to the cases where only optical bypass and only trusted relay are applied, respectively.
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来源期刊
CiteScore
9.40
自引率
16.00%
发文量
104
审稿时长
4 months
期刊介绍: The scope of the Journal includes advances in the state-of-the-art of optical networking science, technology, and engineering. Both theoretical contributions (including new techniques, concepts, analyses, and economic studies) and practical contributions (including optical networking experiments, prototypes, and new applications) are encouraged. Subareas of interest include the architecture and design of optical networks, optical network survivability and security, software-defined optical networking, elastic optical networks, data and control plane advances, network management related innovation, and optical access networks. Enabling technologies and their applications are suitable topics only if the results are shown to directly impact optical networking beyond simple point-to-point networks.
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