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 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.
Quantum key distribution (QKD) is a symmetric key exchange mechanism designed to enhance the security of current communication systems. Although QKD provides unconditional security, it also comes with deployment challenges. One challenge is the distance limitation between the transmitter and receiver, which restricts the large-scale adoption of QKD. To overcome this, trusted relays are used as intermediate nodes, allowing QKD to evolve from distance-limited point-to-point connections to unlimited QKD networks (QKDN). With an increasing deployment of QKD and a growing number of applications requesting keys, quality of service (QoS) constraints must be set for efficient key resource management to alleviate the risk of rejecting application requests. In this work, we integrate key delivery delay and maximum requested key size as QoS constraints in a novel key allocation algorithm built on three QKDN layers – quantum, key management and service. Moreover, we design key relaying using quantum key pools and virtual quantum key pools as storage mechanisms. We use static and dynamic weights for relay path computation and evaluate their impact on the proposed key allocation strategies with QoS constraints and find that static weights show a good overall performance for QKDN, while performance with dynamic weights varies based on historical key consumption data.
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.
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.
Quantum key distribution (QKD) is an encrypted communication technique based on the principles of quantum mechanics that ensures communication security by exploiting the properties of quantum states. Currently, the transmission efficiency of the QKD system is low. Trusted relay technology is used to solve this problem and achieve long-distance transmission. However, trusted relaying alone cannot decrypt the issues of poor link stability and the low utilization of key resources. To further optimize the system performance, we propose a dynamic routing algorithm. One of the improvement schemes includes the following: firstly, an adjustable-size quantum key pool (QKP) is designed, which can dynamically adjust the size of the refreshing pool according to the actual demand. Secondly, the utilization of key resources is improved by using the residual quantum key model to dynamically obtain the remaining key amount in the QKP and set the key amount threshold. We calculate the link-blocking probability and track the blocking intensity and blocking entry by combining the Poisson process, thus realizing the evaluation of the link stability. Finally, the number of remaining keys in the QKP and the link-blocking probability combine with the random wandering model as the basis of the route selection for the QKD dynamic routing algorithm to achieve efficient key path selection. We validated the algorithm by comparing it with other algorithms on the Mininet simulation platform, and the algorithm proved to have a better performance in terms of congestion avoidance, delay reduction, and improved QKD efficiency. This scheme provides a novel and efficient way to solve the problems in existing QKD systems. It effectively improves the transmission efficiency and strengthens the system’s security by dynamically obtaining the critical volume, accurately evaluating the link state, and selecting the optimal critical path.
Quantum secure communication networks based on quantum key distribution (QKD) technology are gradually improving, which can provide remote and networked key services for multiple users. This paper proposes a key distribution solution for latency and resource optimization in trusted relay QKD networks. In this scheme, the key distribution process between trusted relay nodes is presented as a joint optimization problem by considering the constraints of service delay, bandwidth, path resource consumption, quality loss and remaining quantum key quantity. In this paper, we treat key distribution as a bi-objective minimization problem, maintaining a trade-off between service delay and path resource consumption. Specifically, we propose a dynamic key distribution framework based on linear programming and particle swarm optimization. Simulation results show that the key distribution path selection in this scheme can be adjusted according to the service delay, key quality, and path resource consumption. Compared with the Random and customized OSPF policies, this scheme has higher performance. More specifically, the solution reduced average service latency by 27% while reducing path resource consumption by 560%.
The current power service communication relies on classical cryptographic systems, which is vulnerable to attacks from quantum computers. The emerging quantum key distribution (QKD) technology offers information theoretical security, which makes it a promising solution for securing the power backbone communication network. However, integrating QKD and classical power communication on the same fiber can result in significant interference. The primary challenge is to ensure the success rate of QKD and the quality of service (QoS) of power services simultaneously. To address this challenge, this article proposes a network slicing algorithm based on hierarchical routing and dynamic resource allocation (HRDRA). Specifically, a multi-constrained acyclic k shortest path algorithm based on the hierarchical mechanism is developed to achieve differentiated resource mapping of QKD and power service slices. Furthermore, a slicing resource allocation scheme based on chance constrained optimization is designed to improve the flexibility and utilization of resources. Simulation results indicate that the proposed algorithm effectively guarantee the isolation of QKD and power services, and achieve a high key exchange success rate and better QoS for power services.