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%.
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%.
There is a need to ensure unconditionally secure communications between different sites of an organization. We use quantum key distribution (QKD) protocol to provide a continuous stream of secret key bits to each communicating pair for message encryption through one-time-pad (OTP) cryptography. Due to long distance between different sites, trusted nodes are used to relay each service key in a hop-by-hop manner from one end node to another end node of a communicating pair. In a QKD network, routes for key relaying can be affected by availability of relay key bits at trusted nodes. Also, relay key allocation among different routes can impact security. We consider the scenario of supporting multiple communicating pairs, where each pair demands delivery of a certain service key rate across the QKD network, and trusted nodes may not have sufficient relay key rates to perform bitwise encryption to protect the service key. Hence, there is a need to allocate the limited relay key bits to meet all service key delivery demands while considering its effects on security. We propose to perform jointly routing and relay key allocation to minimize attack success probability. We have formulated the joint problem as an optimization and further proposed an efficient algorithm to find the optimal solutions. We have evaluated the proposed algorithm to confirm its ability and efficiency in finding optimal routes and relay key allocations. For the specific network topology that we have adopted, results show that the minimum number of required trusted nodes increases linearly when end nodes are added to the system. Furthermore, we can achieve a higher security level by adding more trusted nodes in a QKD network. But increasing the number of trusted nodes beyond the minimum requirement may not continue to reduce significantly the attack success probability.
This study proposes a group key service node placement method for quantum key distribution (QKD) networks based on partially trusted relays, aiming to optimize network structure, improve key distribution efficiency, reduce communication delay, and ensure transmission integrity and confidentiality. Based on graph theory, a key information model for the quantum key distribution network is established, which defines node types, functions, and connectivity. Leveraging the secure transmission protocol of quantum keys, the unconditional security of the key during transmission is ensured. Furthermore, this study proposes a QKD network architecture incorporating partially trusted relays, which combines trusted and untrusted relay technologies. An improved p-median model is introduced and solved using a greedy algorithm to ensure secure quantum key distribution and optimal deployment of group key service nodes. Experimental results demonstrate that the location of group key service nodes in quantum key distribution network ensures the minimum number of key service nodes and minimizes the path length from network demand nodes to group key service nodes. Furthermore, this method significantly improves the key distribution efficiency, success rate, security, energy consumption, resource consumption, network coverage, and blind area of quantum key distribution network.
ABSTRACT Quantum key relay over trusted relay nodes is a practical approach to overcoming the distance limitation of quantum key distribution (QKD) protocols in quantum-secured networking. However, the processing delay incurred by the quantum key relay function increases the quantum key response delay (KRD) which serves as a representative quality-of-service (QoS) metric for quantum-secured services. This QoS degradation becomes more pronounced in large-scale quantum-secured networks. To address this issue, we investigate a proactive quantum key relay algorithm that relays and prepares quantum keys for pairs of QKD nodes prior to requests for quantum-secured services. By jointly considering the length of the relay path, the available quantity of quantum keys, and the remaining lifetimes of the quantum keys, the proposed algorithm selects a pair of QKD nodes and performs proactive quantum key relay to establish a quantum key for the selected pair. The proposed algorithm enables more flexible operation by sequentially dividing the proactive quantum key relay algorithm into two parts: one for a relatively short distance pair of QKD nodes and the other for a long-distance pair of QKD nodes. The simulation results demonstrate that, compared with the on-demand quantum key relay algorithm, the proposed algorithm achieves a relative reduction of up to 89.7% in the modeled KRD, accompanied by a corresponding relative decrease of 13.9% in the provisioning ratio of quantum-secured service. Overall, these findings confirm the effectiveness of the proposed proactive quantum key relay algorithm in achieving short-latency quantum-secured networking.
Efficient and scalable quantum key scheduling remains a critical challenge in trusted-relay Quantum Key Distribution (QKD) networks due to imbalanced key resource utilization, dynamic key consumption, and topology-induced congestion. This paper presents a Q-learning-based adaptive routing framework designed to optimize quantum key delivery in dynamic QKD networks. The model formulates routing as a Markov Decision Process, with a compact state representation that combines the current node, destination node, and discretized key occupancy levels. Reward function is designed to jointly penalize resource imbalance and rapid key depletion while promoting traversal through links with sustainable key generation, guiding the agent toward balanced and congestion-aware decisions. Compared to Dijkstra, the Q-learning scheduler achieves significantly lower delivery latency, more effective key resource utilization, and greater reliability: maintaining 45.8 vs 118.5 hops in average delay under heavy load, sustaining 74.5\% vs 61.5\% in average key utilization, and reducing the failure ratio to 7.2\% vs 41.5\%, collectively confirming its advantages in scalability, congestion resilience, and resource-efficient decision making.
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 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.