As a prototype of quantum communications, quantum key distribution (QKD) is recommended for integration into the existing optical infrastructures to enable scalable quantum networking. This necessitates the development of supporting resource allocation strategies for carrier-grade operations. In this work, we propose a quantum-aware RWA framework with dual-granularity power control (QRA-PC) to mitigate quantum-classical interference under hybrid network constraints. In a 9-node mesh network with 1 GHz discrete-variable QKD systems coexisting in the C-band, QRA-PC with local power control mode achieves an average SKR of 891.9 kb/s at a traffic load of 50 erlangs, compared to the first-fit baseline of 50.4 kb/s. This result is achieved without incurring any classical traffic blocking.
As a prototype of quantum communications, quantum key distribution (QKD) is recommended for integration into the existing optical infrastructures to enable scalable quantum networking. This necessitates the development of supporting resource allocation strategies for carrier-grade operations. In this work, we propose a quantum-aware RWA framework with dual-granularity power control (QRA-PC) to mitigate quantum-classical interference under hybrid network constraints. In a 9-node mesh network with 1 GHz discrete-variable QKD systems coexisting in the C-band, QRA-PC with local power control mode achieves an average SKR of 891.9 kb/s at a traffic load of 50 erlangs, compared to the first-fit baseline of 50.4 kb/s. This result is achieved without incurring any classical traffic blocking.
Optical communications provide high capacity and scalability, while quantum communications, particularly through quantum key distribution (QKD), enable information-theoretic security. However, it still remains challenging to deliver both high throughput communication and long-term security within a hybrid quantum-classical optical network. Specifically, classical optical resources can be reallocated to support QKD, aiming to achieve synergistic resource utilization that surpasses the sum of individual functionalities. In this work, we formulate a networking model that captures the resource allocation constraints, aiming to figure out the necessary conversion of classical optical resources to QKD capacity while maintain the connectivity of classical optical communication. Based on that, we propose a synergistic resource allocation strategy, implemented through heuristic routing, wavelength assignment, and power configuration (SRWP) algorithms. Simulation results demonstrate that the proposed SRWP algorithm, with the objective of network-wide average secret key rate (SKR) maximization (SRWP-ARM), enhances the average SKR from the order of kbit/s to Mbit/s at GHz-level pulse repetition rates. In a 9-node mesh network topology with 50 km links, the algorithm achieves this gain with zero service blocking under a traffic load of 100 erlangs. At a higher load of 300 erlangs, it maintains a service blocking probability as low as 1.24% while still achieving an average SKR of 18.05 kbit/s. This represents the best trade-off between classical service connectivity and secret key generation across all evaluated algorithms.
The demand for secure communication in the age of quantum technologies has driven progress in quantum key distribution (QKD) techniques for optical networks. This research addresses the issues of high blocking probabilities (BPs) and the proper utilization of quantum resources in varying network loads by introducing a novel heuristic approach, termed dynamic security-aware quantum resource allocation (D-SQRA), designed for dynamic resource allocation in QKD-enabled optical networks. We propose two D-SQRA algorithms to employ an adaptive resource assignment (RA) strategy that concurrently addresses routing, wavelength, and time-slot selection while dynamically modifying security levels according to the real-time network load and resource availability. We evaluate the proposed D-SQRA performance against two conventional methods, namely, fixed security quantum resource allocation (F-SQRA) and baseline quantum resource allocation (B-QRA). We discuss the results for NSFNET and UBN24 topologies for network security performance metrics such as network security performance (NSP), BP, quantum key utilization (QKU), and time-slot utilization. The results show that the proposed D-SQRA algorithms provide significant improvement with respect to conventional techniques in addressing proper resource utilization and management by reducing BPs of the new incoming connection requests.
Quantum Key Distribution is increasingly being integrated into existing classical communication networks. However, the coexistence of classical traffic with quantum signals introduces noise due to nonlinear effects, which can degrade the performance of the quantum channel. In this work we analyze the impact of launch power control protocols on network resource allocation algorithms in mitigating this interference. Our study aims at enhancing the quality of the quantum channel in hybrid QKD-classical optical networks.
Abstract Quantum key distribution (QKD) is gradually evolving from dedicated-link deployment toward networked integration with existing optical network infrastructures. In quantum–classical co-propagation scenarios, the quality of quantum links is readily affected by noise interference and device non-idealities, making efficient routing and resource allocation in multi-node networks a critical issue. To address this problem, this paper proposes a security-aware, data-driven QKD routing and admission control framework for software-defined networking (SDN)-controlled quantum–classical integrated optical networks. In the proposed framework, a variational quantum classifier (VQC) is employed as a link-state pre-screening mechanism, and the detection results are further used to support candidate path screening, routing decision-making, and resource allocation. In addition, the actual key generation capability of each path is further validated by incorporating the QKD protocol procedure into the decision process. Simulation results show that, compared with conventional baseline methods, the proposed method achieves stable performance under varying traffic loads, non-ideal conditions, and larger network scales, while yielding moderate improvements in system blocking ratio, average quantum signal-to-noise ratio (QSNR), and final key length.
Resource Allocation in quantum key distribution-enabled optical networks (QKD-ON) is an NP-hard combinatorial problem. Classical heuristics are greedy and suffer high blocking under dynamic traffic and security constraints, while deep reinforcement learning (DRL) methods can reduce blocking but introduce a processing bottleneck because their inference latency is often slower than the operational timescales of QKD-ON. We introduce hybrid quantum–classical frameworks using the quantum approximate optimization algorithm (QAOA) and variational quantum eigensolver (VQE) to perform request routing. The scheduling problem is encoded as a hamiltonian with penalty terms for wavelength and timeslot conflicts. We evaluate the approach on NSFNet and UBN topologies under dynamic traffic with time division multiplexing (TDM) and wavelength-time division multiplexing (WTDM). Our quantum-enhanced algorithms yield comparable or lower blocking with reduced inference latency, which can improve further on quantum hardware.
Quantum Key Distribution has become a mature quantum technology that has outgrown dedicated links and is ready to be incorporated into the classical infrastructure. In this scenario with multiple potential nodes, it is crucial having efficient ways to allocate the network resources between all the potential users. We propose a simple method for routing and wavelength assignment in wavelength multiplexed networks in which classical and quantum channels coexist. The proposed heuristics take into account the specific requirements of quantum key distribution and focus on keeping at bay the contamination of the quantum channels by photons coming from the classical signals from non-linear processes, among others. These heuristics reduce the shared path between classical and quantum channels and improve the signal-to-noise ratio in the quantum channels, improving their quantum key rate. We compare the results to the usual classical RWA approach.