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.
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 (QKD) has potential of providing long-term security as it is based on the fundamental principles of quantum mechanics. Security of information transmitted through optical networks has attracted attention recently due to its vulnerability to attacks post quantum computers. Hence, the integration of QKD into optical networks can significantly improve the security of existing and future optical networks. In QKD-secured optical networks, the quantum channel and the classical channel are integrated into a single optical fiber to reduce the deployment cost of the network infrastructure. However, due to limited network resources in a single optical fiber, the efficient provisioning of network resources (wavelengths and time slots) and blocking are two major issues in such networks. In this work, a resource assignment strategy with scheduling, namely, resource assignment with scheduling (RA-WS) has been proposed for utilization of network resources efficiently. In the RA-WS strategy, the QKD lightpath requests (QLPRs) have been served according to the proposed scheduling criterion. Moreover, the proposed scheduling criterion for routing, wavelength and time-slot assignment (RWTA) can reduce the effect of QLPRs blocking because of the limited network resources. The performance of the proposed RA-WS strategy has been analyzed in terms of blocking probability (BP), success probability of update secret key (SPUSK), and time-slot utilization ratio (TSUR) with different reserved wavelengths for quantum signal channel (QSCh), i.e.,WQand different time slots (ntr). Simulations performed on NSFNET network topology indicate that the RA-WS strategy performs better than the baseline strategy, i.e., resource assignment without scheduling (RA-WOS) in terms of all the considered metrics.
ABSTRACT With the rising demand for secure and reliable telecommunication networks, efficient resource allocation strategies in quantum key distribution‐based software‐defined optical networks (SDONs) are becoming essential. In this research, we propose a heuristic adaptive quantum routing (RWTA_AQR) algorithm for routing, wavelength and timeslot assignment. RWTA_AQR utilises the FirstFit algorithm to assign wavelengths in both contiguous and noncontiguous timeslots for optimal resource utilisation based on the priority. To verify its effectiveness, the proposed RWTA_AQR is tested on NSFNET and UBN24 network topologies under diversified traffic models, towards low as well as high demand, network congestion scenarios. We use network security performance (NSP), success ratio of connection requests, timeslot utilisation, quantum key utilisation, blocking probability (BP) and security downgrade ratio as metrics to prove its effectiveness against the existing methods based on flexible security level, strict security level and classical approach. The results demonstrate that RWTA_AQR performs better by allowing NSP of up to 90% and having the lowest BP (below 10%) at lower traffic load. The proposed solution provides a systematic trade‐off in security and resource utilisation with controlled overhead for improving the performance of QKD‐SDONs in dynamic resource‐constrained environments.
Abstract Quantum key distribution (QKD) optical networks, relying on the information-theoretic security guaranteed by the fundamental laws of quantum physics, have become a core solution for ensuring data transmission security in critical fields such as finance and energy. However, QKD optical networks have inherent characteristics like severe resource constraints, dynamic changes in network environments. The collaborative optimization of routing, wavelength, and time-slot assignment (RWTA) has thus become a key bottleneck restricting their practical deployment. Traditional algorithms suffer from high complexity and poor adaptability in large-scale dynamic networks, while existing deep reinforcement learning (DRL) schemes insufficiently consider network security states, failing multi-objective co-optimization. Therefore, this paper proposes a multi-objective secure proximal policy optimization algorithm (MOS-PPO) based on DRL to solve the routing, wavelength, and time slots assignment problem in QKD optical networks. The MOS-PPO algorithm expands the state space by introducing a network security state vector that includes quantum bit error rate, risk coefficient, node capacity, and processing capability. It designs a multi-objective reward function, and establishes a security constraint mechanism to achieve the collaborative optimization of blocking probability (BP), resource utilization (RU), and security performance. Simulations on NSFNET and UBN24 topologies show MOS-PPO outperforms DRL-PPO algorithm, Security-aware Load balancing, first fit algorithm, and random fit algorithm. On NSFNET, average BP drops by 20.4%, 22.1%,28.4%, 36.7% and RU rises by 4.0%,3.9%, 22.2%, 31.0%, on UBN24, BP decreases by 9.3%, 11.4%, 18.8%, and 27.4% and RU increases by 3.8%, 21.2%, 10.3%, and 29.5%, with higher stable security margins. This study verifies the high adaptability and multi-objective optimization ability of the MOS-PPO algorithm in dynamic network environments, providing an efficient RWTA solution for the practical deployment of QKD optical networks.
Abstract Quantum key distribution (QKD) optical networks can provide more secure communications. However, with the increase of the QKD path requests and key updates, network blocking problems will become severe. The blocking problems in the network can become more severe because each fiber link has limited resources (such as wavelengths and time slots). In addition, QKD optical networks are also affected by external disturbances such as data interception and eavesdropping, resulting in inefficient network communication. In this paper, we exploit the idea of protection path to enhance the anti-interference ability of QKD optical network. By introducing the concept of security metric, we propose a routing wavelength and time slot allocation algorithm (RWTA) based on protection path, which can lessen the blocking problem of QKD optical network. According to simulation analysis, the security-metric-based RWTA algorithm (SM-RWTA) proposed in this paper can substantially improve the success rate of security key (SK) update and significantly reduce the blocking rate of the network. It can also improve the utilization rate of resources such as wavelengths and time slots. Compared with the non-security-metric-based RWTA algorithm (NSM-RWTA), our algorithm is robust and can enhance the anti-interference ability and security of QKD optical networks.
With the rapid development of optical networks and the increasing amount of data transmission, information security has become a critical concern. Quantum key distribution can theoretically provide security for data encryption key distribution, and its integration into optical networks can enhance overall security. To reduce deployment costs, Wavelength Division Multiplexing is used to combine quantum and classical signals. However, limited wavelength resource necessitate the use of Time Division Multiplexing. How to efficiently allocate the multidimensional resources, such as wavelength, time slots, and encryption keys, has become a key issue in the design of secure optical networks. This paper proposes a Security-Level-based routing, wavelength, and time slot assignment strategy for optical networks. To evaluate the effectiveness of the proposed strategy, we introduce a new metric called Average Key Consumption. This metric allows us to assess key usage efficiency and network performance. We analyze the impact of different Average Key Consumption values on network resource allocation. Simulation results demonstrate that the Security-Level-based routing, wavelength, and time slot assignment strategy outperforms other strategies in handling high security demands.
Data transmission with optical fiber is vulnerable to eavesdropping. Moreover, conventional key distribution technology suffers from increasing computational power and upgraded attack algorithms. To address these issues, quantum key distribution (QKD), a quantum technology that secures secret information (such as a cryptographic key) exchange between two parties, can be used to guarantee secure data transmission. Integrating QKD into existing wavelength division multiplexing optical networks has been verified through a series of experiments, which contribute to ensuring network security and saving fiber resources. This paper addresses the resource assignment problem in QKD-enabled optical networks. First, a QKD-enabled optical network architecture is introduced. A small fraction of wavelength channels are segmented into multiple time slots with optical time division multiplexing technology to construct quantum key channels (QKChs) and measuring-basis channels, and then the remaining wavelengths can construct traditional data channels. Second, a static routing, wavelength, and time-slot assignment (RWTA) strategy is proposed and verified by the integer linear programming formulation and a heuristic algorithm. In the RWTA, QKChs are assigned for service requests according to the security levels specified by relevant key-updating periods. Thus, the secret keys for data encryption can update periodically to enhance security. Simulation results indicate that there is a trade-off between security (i.e., security levels and security-level types) and resource utilization.