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arXiv:2209.11957 · IEEE Internet of Things Journal

Cooperative Resource Management in Quantum Key Distribution (QKD) Networks for Semantic Communication

Rakpong Kaewpuang, Minrui Xu, Wei Yang Bryan Lim, Dusit Tao Niyato, Han Yu, Jiawen Kang, Xuemin Shen

Published Aug 3, 2023• 28 citations
arXivHTMLPDF

Abstract

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.

DOI
10.1109/jiot.2023.3301033

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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.
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.
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Quantum Key Distribution (QKD) has demonstrated unique and significant advantages in secure communication. In particular, Measurement-Device-Independent QKD (MDI-QKD), which is independent of measurement devices, increases data transmission distances and addresses the issue of low security in trusted relays. Therefore, in this work, we investigate QKD networks based on trusted and untrusted relays over optical backbone networks, providing a cost-optimal solution for the deployment and implementation of QKD networks. Specifically, this paper describes the QKD network and defines a new cost model, which not only fully considers the diverse impact factors of deployment costs but also meets the requirements for sharing network elements in response to different QKD chain requests. Based on cost model, this paper further proposes a cost-optimal heuristic algorithm for hybrid QKD network deployment, which can provide an economical and secure deployment solution for QKD networks. Extensive simulation experiments are conducted and the experimental results show that the proposed method outperforms current mainstream QKD network deployment algorithms in both deployment cost and security. Moreover, as the network scale increases, the advantages of our algorithm become more pronounced. Compared to mainstream algorithms, our method achieve an improvement of 17.7% -64.3% in cost savings and 1.19 to 3.24 times in security levels.
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.