Quantum communication is a promising technique for enhancing the information security. However, the limited availability of quantum keys due to low generation rates still remains a challenge in the quantum key distribution of power systems. To address this issue and optimize the utilization of quantum resources in the gradually developed quantum-secured power communication systems, this article proposes a hybrid resource optimization method by leveraging network virtualization technologies. First, we present a virtualized architecture using software-defined networking and network function virtualization to support multiapplication scenarios in power system communications. Subsequently, a two-stage resource optimization strategy is proposed to manage both classical and quantum resources. At the first stage, we design a network slicing scheme for allocating classical communication resources, such as channel capacity and time delay. This scheme aims to segregate information flows from applications with diversified quality of service requirements. At the second stage, encryption resources are allocated by matching limited quantum keys with communication requests with different priorities, thereby improving the overall performance of quantum-classical power communication systems. Finally, we construct a cosimulation testbed to validate the effectiveness of the proposed method through case studies.
Quantum communication is a promising technique for enhancing the information security. However, the limited availability of quantum keys due to low generation rates still remains a challenge in the quantum key distribution of power systems. To address this issue and optimize the utilization of quantum resources in the gradually developed quantum-secured power communication systems, this article proposes a hybrid resource optimization method by leveraging network virtualization technologies. First, we present a virtualized architecture using software-defined networking and network function virtualization to support multiapplication scenarios in power system communications. Subsequently, a two-stage resource optimization strategy is proposed to manage both classical and quantum resources. At the first stage, we design a network slicing scheme for allocating classical communication resources, such as channel capacity and time delay. This scheme aims to segregate information flows from applications with diversified quality of service requirements. At the second stage, encryption resources are allocated by matching limited quantum keys with communication requests with different priorities, thereby improving the overall performance of quantum-classical power communication systems. Finally, we construct a cosimulation testbed to validate the effectiveness of the proposed method through case studies.
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.
The growing integration of power grids with communication networks underscores the critical importance of cybersecurity. Quantum key distribution (QKD) offers a potent approach to secure power information based on physics laws. However, the challenge of limited quantum keys due to low key rates remains unresolved, necessitating the optimal planning of QKD networks. Therefore, this paper proposes a QKD network planning method to address uncertainties in power communication. First, the fiber QKD-based communication network is introduced. Then, the QKD network planning problem is formulated as a two-stage stochastic mixed-integer linear programming (MILP) model. The first stage models the quantum device deployment considering QKD processes and investment budgets. The second stage takes demand response as an example, considering scenario-dependent communication requests that fluctuate with the output of renewable energy resources. Finally, the proposed method is validated by a modified IEEE 30-bus system, with numerical results verifying its effectiveness in improving power cybersecurity.
With the development of smart grids, the demand for cybersecurity is increasing rapidly. Quantum Key Distribution (QKD), which can theoretically achieve secure information transmission, has the potential to enhance the security of power communication. To overcome the structural limitations and resource constraints of current QKD-based communication schemes, this paper proposes a multi-resource hybrid QKD-based communication scheme for power grids. This scheme meets the diverse secure communication needs of power systems through the coordinated utilization of multiple QKD resources. First, the advantages and disadvantages of satellite, fiber, and wireless QKD methods, along with their respective application scenarios, are analyzed. Then, considering the synergistic effects of hybrid QKD and the varied demands of power businesses, a quantum resource deployment optimization model is established. This model aims to minimize the system’s information risk index and is reformulated as a solvable mixed-integer linear programming (MILP) problem. Finally, the effectiveness of the proposed scheme is validated using a modified IEEE RTS-79 test system and two real-world power communication systems. By analyzing on sensitivity, adaptability, scalability and IoT applications of various QKD methods, this study provides valuable insights for the large-scale deployment of quantum-secure power communication networks in the future.
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.
Abstract Quantum networks provide both security and faster communication; however, they face critical challenges in terms of dynamic resource allocation and maintaining robust security. Current static allocation methodologies frequently lead to excessive latency and attack vulnerabilities, which restrict performance and scalability. To address these challenges, this article presents a secure and adaptive resource allocation outline for quantum networks, merging quantum-enhanced security protocols with real-time optimization. The framework utilizes Quantum Key Distribution - Single Center Method (QKD-SCM) to exchange secure and scalable keys. and the Stochastic Programming and the Cooperative-Qubit-Allocation-Problem (SP-CQAP), which addresses dynamic resource allocations. High-fidelity entangled resources are managed with the Fidelity Maintenance Scheme Based on Prioritized Purification (FMSPP), and congestion is avoided using Self-Adaptive and Content-Based Scheduling (CACS). The proposed framework was evaluated using NS-3.30.1 and Python 3.7.4, running on Ubuntu 18.4 LTS. In comparison to already-existing methodologies within the segment, the proposed framework demonstrated reduced latency of 20 ms, energy efficiencies of 90%, a quantum key distribution success rate of 90%, and resource utilization equating to 70%. The findings demonstrate the promise of quantum-enhanced wireless communication through dynamic resource allocation for safe, low-latency, and high-performance networking. Removed: security enhancement implied earlier.
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.