Datacenter networks (DCNs) with cloud–edge collaboration are emerging to satisfy the communication, computation, and caching (3C) requirements of future services such as cloud-based IoT services. However, the enroute data over DCNs with cloud–edge collaboration is likely to suffer from cyberattacks such as eavesdropping. A large number of services require not only 3C resources, but also cryptographic resources for encryption to ensure high security. Quantum key distribution (QKD) is a practical approach to provide secret keys for remote users with information-theoretic security against attacks from quantum computing. A QKD-secured DCN (QKD-DCN) with cloud–edge collaboration can be deployed to satisfy the communication, computation, caching, and cryptographic (4C) requirements of services. This article innovatively solves the new 4C resource-allocation (4CRA) problem in the network to minimize the cryptographic resource consumption. It formulates an integer linear programming (ILP) model and proposes a heuristic cryptographic-dependent 4CRA algorithm to find optimal solutions. The proposed algorithm is compared with two baseline 4CRA algorithms which, respectively, consider the minimized service delivery latency and the first-fit resource availability. Analytical simulations show that the proposed algorithm minimizes the key-resource-consumption ratio and the average key-resource consumption under static and dynamic traffic scenarios in different network topologies.
Datacenter networks (DCNs) with cloud–edge collaboration are emerging to satisfy the communication, computation, and caching (3C) requirements of future services such as cloud-based IoT services. However, the enroute data over DCNs with cloud–edge collaboration is likely to suffer from cyberattacks such as eavesdropping. A large number of services require not only 3C resources, but also cryptographic resources for encryption to ensure high security. Quantum key distribution (QKD) is a practical approach to provide secret keys for remote users with information-theoretic security against attacks from quantum computing. A QKD-secured DCN (QKD-DCN) with cloud–edge collaboration can be deployed to satisfy the communication, computation, caching, and cryptographic (4C) requirements of services. This article innovatively solves the new 4C resource-allocation (4CRA) problem in the network to minimize the cryptographic resource consumption. It formulates an integer linear programming (ILP) model and proposes a heuristic cryptographic-dependent 4CRA algorithm to find optimal solutions. The proposed algorithm is compared with two baseline 4CRA algorithms which, respectively, consider the minimized service delivery latency and the first-fit resource availability. Analytical simulations show that the proposed algorithm minimizes the key-resource-consumption ratio and the average key-resource consumption under static and dynamic traffic scenarios in different network topologies.
The cloud services requiring communication, computing and caching (3C) resources are supported by datacenter networks (DCNs). The service security is threatened due to the development of quantum computers. Quantum key distribution (QKD) technology promises to share secret keys as cipher resources between remote users with information-theoretic security. The quantum cloud is illustrated which is realized by the QKD-secured cloud datacenter network. In the quantum cloud, the communication, computing, caching and cipher (4C) resources are provided for data transmission, processing, storing and encryption. To solve the newly emerged 4C resource coordination problem, a 4C-oriented control architecture is designed and the heuristic algorithms for securing service function chains are innovatively proposed. The simulation results show that the proposed algorithms can achieve the great service success ratio performance compared with the baseline.
Quantum Key Distribution (QKD) technology leverages its inherent security advantages to ensure information-theoretic security for data transmission in networks. However, existing QKD networks still face critical challenges, including network congestion that stems from limited key resources and uneven resource allocation methods. Thus, in this paper, we focus on the issue of network congestion caused by bottleneck links and aim to achieve load balancing. Considering the limited key resources, we first introduce the key resource utilization ratio as an indicator of bottleneck links and formulate the resource allocation problem as an Integer Linear Programming (ILP) problem. To deal with the complexity of the ILP problem, especially in large-scale network scenarios, we design a heuristic algorithm that can obtain near-optimal solutions within polynomial time. Finally, we implement the proposed key resource allocation scheme in various real-world network topologies using a full-stack quantum network simulator. Compared to the existing algorithms, extensive results show that our method can reduce key resource consumption by up to 50% on bottleneck links and improve the robustness of QKD networks when facing burst quantum key agreement requests.
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.
Edge computing is a leading trend in the deployment of computation and networking infrastructures, where processing is done closer to the users, compared to more traditional cloud-based solutions relying on remote data centers. On the other hand, Quantum Key Distribution (QKD) technologies, offering unconditional security between the communicating parties, is expected to become affordable in the near future and it will unlock new opportunities, e.g., for applications with long-term confidentiality requirements. In this paper we study how to enable ETSI ISG QKD key delivery within an ETSI MEC edge computing scenario, in the practical use case of cloud-native applications based on Function-as-a-Service (FaaS). This work is part of the activities of the PON project “Development of quantum systems and technologies for IT security in communication networks” (QUANCOM) which aims to the realization of a metropolitan quantum communication network through the collaboration between universities, research centers and companies operating in the communication market area.
The increasing focus on privacy and security in 6G networks, which are intelligence-native, necessitates the use of quantum key distribution-secured semantic information communication (QKD-SIC) to protect confidential data. In QKD-SIC systems, edge devices connected via quantum channels can efficiently encrypt semantic information from the semantic source, and securely transmit the encrypted semantic information to the semantic destination. In this article, we consider an efficient resource (i.e., quantum key distribution (QKD) and KM wavelengths) sharing problem to support QKD-SIC systems under the uncertainty of semantic information generated by edge devices. In such a system, QKD service providers offer QKD services with different subscription options to the edge devices. The QKD services are envisioned to follow cloud computing that has the subscription in the reservation and on-demand options, i.e., for long and short (immediate) terms, respectively. As such, to reduce the cost for the edge device users, we propose a QKD resource management framework for the edge devices communicating semantic information. The framework is based on a two-stage stochastic optimization model to achieve optimal QKD deployment. Moreover, to reduce the deployment cost of QKD service providers, QKD resources in the proposed framework can be utilized based on efficient QKD-SIC resource management, including semantic information transmission among edge devices, secret-key provisioning, and cooperation formation among QKD service providers. In detail, the formulated two-stage stochastic optimization model can achieve the optimal QKD-SIC resource deployment while meeting the secret-key requirements for semantic information transmission of edge devices. Moreover, to share the cost of the QKD resource pool among cooperative QKD service providers forming a coalition in a fair and interpretable manner, the proposed framework leverages the concept of Shapley value from cooperative game theory as a solution. Experimental results demonstrate that the proposed framework can reduce the deployment cost by about 40% compared with existing noncooperative baselines.