The convergence of quantum key distribution (QKD) and classical optical networks faces a serious challenge of dynamic resource allocation. In this paper, a three-dimensional resource optimization method based on the improved multipath A* algorithm is proposed, which solves the inefficiency problems brought by path redundancy of the traditional KSP algorithm and blind search of BFS/DFS by pre-computing node-level heuristic functions with dynamic link weight adjustment mechanism. A joint path-time slot-wavelength-key resource allocation model is constructed on NSFNET topology, and the experimental results show that the algorithm reduces the demand blocking rate, improves the success rate of high security transmission, and reduces the computational overhead. The results provide an efficient heuristic framework for the dynamic scheduling of quantum optical network resources, which significantly improves the reliability and security of quantum key relay service.
The convergence of quantum key distribution (QKD) and classical optical networks faces a serious challenge of dynamic resource allocation. In this paper, a three-dimensional resource optimization method based on the improved multipath A* algorithm is proposed, which solves the inefficiency problems brought by path redundancy of the traditional KSP algorithm and blind search of BFS/DFS by pre-computing node-level heuristic functions with dynamic link weight adjustment mechanism. A joint path-time slot-wavelength-key resource allocation model is constructed on NSFNET topology, and the experimental results show that the algorithm reduces the demand blocking rate, improves the success rate of high security transmission, and reduces the computational overhead. The results provide an efficient heuristic framework for the dynamic scheduling of quantum optical network resources, which significantly improves the reliability and security of quantum key relay service.
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.
Abstract With the rapid development of quantum communication technology, quantum key distribution (QKD) provides unconditional secure communication based on the principles of quantum mechanics. In the scenario of multi-service concurrency, it faces the challenges of dynamic resource allocation and complex network scheduling. The traditional key pool management mechanism has problems such as low key resource utilization and difficulty in coordinating multi-dimensional constraints in path optimization, which cannot meet the dynamically changing service quality requirements. This study proposes a quantum key pool architecture with dynamic resource management capabilities. The architecture adopts hierarchical key pool management and adds key recovery mechanism and key dynamic transfer function. For the path optimization problem under multiple constraints, the Lagrangian dual decomposition method is used to establish a mathematical model. The model considers multiple key factors such as bandwidth and delay, and designs an efficient heuristic algorithm to solve the optimal routing strategy. The simulation results show that the proposed algorithm has good performance in terms of service request success rate, key resource utilization, key remaining rate, etc. This study provides a new idea for key distribution and resource allocation in quantum networks, which will help promote the further development of quantum communication technology.
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.
Quantum key distribution (QKD) is a technology that can resist the threat of quantum computers to existing conventional cryptographic protocols. However, due to the stringent requirements of the quantum key generation environment, the generated quantum keys are considered valuable, and the slow key generation rate conflicts with the high-speed data transmission in traditional optical networks. In this paper, for the QKD network with a trusted relay, which is mainly based on point-to-point quantum keys and has complex changes in network resources, we aim to allocate resources reasonably for data packet distribution. Firstly, we formulate a linear programming constraint model for the key resource allocation (KRA) problem based on the time-slot scheduling. Secondly, we propose a new scheduling scheme based on the graded key security requirements (GKSR) and a new micro-log key storage algorithm for effective storage and management of key resources. Finally, we propose a key resource consumption (KRC) routing optimization algorithm to properly allocate time slots, routes, and key resources. Simulation results show that the proposed scheme significantly improves the key distribution success rate and key resource utilization rate, among others.
Currently, with the continuous advancement of network and communication technology, the amount of data carried by the optical network is very huge. The security of high-speed and large-capacity information in optical networks has attracted more and more attention. Quantum key distribution (QKD) provides information-theoretic security based on the laws of quantum mechanics. Introducing QKD into an optical network can greatly improve the security of the optical network. In order to reduce the cost of deployment on QKD infrastructure, quantum signals in QKD and classical signals in optical networks are multiplexed in the same fiber by wavelength-division manner. Moreover, due to the limited wavelength resources in an optical fiber, time-division technology is adopted to construct different kinds of channels in QKD system for efficient utilization of wavelength resources. Under such situation, how to satisfy the security requirements of service requests and complete the efficient scheduling of multi-dimensional resources, i.e., wavelengths and timeslots, is a challenging problem. This paper addresses this problem by considering multi-dimensional routing, wavelength, and timeslot allocation (RWTA) in short-distance quantum key distribution optical networks (QKD-ON), in which any two nodes can directly establish a quantum channel, and the maximum distance between any two nodes is less than the distance that can carry out point-to-point quantum key distribution process. While accommodating services with security requirements in QKD optical networks, to avoid the wavelength time-slot fragmentation caused by the constraints of wavelength consistency and time-slot continuity, we propose a time-window-based security orchestration strategy as well as relative-loss of time continuous compactness based RWTA strategy. We conducted the simulations under various scenarios, e.g., different key updating periods and different distributions on wavelength resources, etc., and the results show that the proposed strategy can achieve better performance compared with the baselines in terms of key success rate, key-updating delay, and blocking probability.
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.