Switching Coordinator: An SDN Application for Flexible QKD-Networks

• URL: http://arxiv.org/abs/2603.13812v1
• Date: Sat, 14 Mar 2026 07:35:04 GMT
• Title: Switching Coordinator: An SDN Application for Flexible QKD-Networks
• Abstract summary: A monitor and control framework for quantum-key-distribution (QKD) networks equipped with switching capabilities was developed.<n>It extracts essential data, such as the switching capabilities of QKD modules, the number of keys stored in buffer queues of the QKD links, and the respective key generation and consumption rates.<n>On the other hand, it allows software-defined networking applications to operate on the collected information and address the cryptographic needs of the network.
• Score: 0.15840308565716285
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: A monitor and control framework for quantum-key-distribution (QKD) networks equipped with switching capabilities was developed. On the one hand, this framework provides real-time visibility into operational metrics. Specifically, it extracts essential data, such as the switching capabilities of QKD modules, the number of keys stored in buffer queues of the QKD links, and the respective key generation and consumption rates along these links. On the other hand, this framework allows software-defined networking (SDN) applications to operate on the collected information and address the cryptographic needs of the network. The SDN applications dynamically adapt the configuration of the switched network to align with its changing demands, e.g.,~prioritizing key availability on critical paths, responding to link failures, or reallocating generation capacity to prevent bottlenecks. This contribution demonstrates that the combination of switched QKD, centralized control, and global optimization strategies enables efficient, policy-driven operation of QKD networks. The cryptographic resources are allocated to maximize performance and resilience while remaining aligned with the specific policies set by network administrators.

Related papers

• Software Defined Networks Key Relay for Large-Scale Quantum Key Distribution Networks [35.61991435985963]
  This work addresses the orchestration of largescale Quantum Key Distribution Networks (QKDNs) using Software Defined Networking (SDN)<n>Building on ETSI and ITU specifications, common best practices and architectures are outlined.<n>Multiple path selection algorithms, based on Dijkstra or a maximum-minimum capacity algorithm, with built-in load balancing are presented.
  arXiv  Detail & Related papers  (2026-08-18T09:01:32Z)
• Deploying and validating a metropolitan QKD secure network: architecture and field performance [76.02413102965598]
  Quantum Key Distribution provides information-theoretic security for key establishment.<n>A metropolitan-scale quantum-secure network between data centers in Milan is reported.<n>Results establish the technical and operational readiness of metropolitan QKD networks for production deployment.
  arXiv  Detail & Related papers  (2026-07-13T15:51:26Z)
• Reinforcement Learning for Quantum Network Control with Application-Driven Objectives [53.03367590211247]
  Dynamic programming and reinforcement learning offer promising tools for optimizing control strategies.<n>We propose a novel RL framework that directly optimize non-linear, differentiable objective functions.<n>Our work comprises the first step towards non-linear objective function optimization in quantum networks with RL, opening a path towards more advanced use cases.
  arXiv  Detail & Related papers  (2025-09-12T18:41:10Z)
• Quantum Key Distribution Networks -- Key Management: A Survey [1.3611372330340248]
  Quantum Key Distribution (QKD) is a promising technology that provides an Information-Theoretically Secure (ITS) solution to the secret-key agreement problem between two remote parties. QKD networks based on trusted repeaters are built to provide service to a larger number of parties at arbitrary distances.
  arXiv  Detail & Related papers  (2024-08-08T16:42:45Z)
• Digital Twin-Assisted Data-Driven Optimization for Reliable Edge Caching in Wireless Networks [60.54852710216738]
  We introduce a novel digital twin-assisted optimization framework, called D-REC, to ensure reliable caching in nextG wireless networks. By incorporating reliability modules into a constrained decision process, D-REC can adaptively adjust actions, rewards, and states to comply with advantageous constraints.
  arXiv  Detail & Related papers  (2024-06-29T02:40:28Z)
• Software-defined quantum network using a QKD-secured SDN controller and encrypted messages [0.0]
  We propose and implement a software-defined network architecture that integrates the QKD SDN Controller within the QKD node. We use quantum keys to secure its communication with SDN agents while optimizing QKD-keys consumption.
  arXiv  Detail & Related papers  (2023-05-22T10:21:33Z)
• Optimization of QKD Networks with Classical and Quantum Annealing [0.7827586118586438]
  Quantum Key Distribution (QKD) hardware is used in a tier 1 provider network. The ensemble of QKD systems needs to be able to exchange as many encryption keys. Redundancy and latency requirements add additional boundary conditions.
  arXiv  Detail & Related papers  (2022-06-28T16:08:12Z)
• An Efficient Routing Protocol for Quantum Key Distribution Networks [9.203625000707856]
  Quantum key distribution (QKD) can provide point-to-point information-theoretic secure key services for two connected users. QOLSR considerably improves quantum key utilization in QKD networks through link-state awareness and path optimization.
  arXiv  Detail & Related papers  (2022-04-29T07:37:45Z)
• Deep Reinforcement Learning for Wireless Scheduling in Distributed Networked Control [37.10638636086814]
  We consider a joint uplink and downlink scheduling problem of a fully distributed wireless control system (WNCS) with a limited number of frequency channels.<n>We develop a deep reinforcement learning (DRL) based framework for solving it.<n>To tackle the challenges of a large action space in DRL, we propose novel action space reduction and action embedding methods.
  arXiv  Detail & Related papers  (2021-09-26T11:27:12Z)
• Fast and Secure Routing Algorithms for Quantum Key Distribution Networks [5.659290426197763]
  We consider the problem of secure packet routing at the maximum achievable rate in Quantum Key Distribution (QKD) networks. We propose a new secure throughput-optimal policy called Tandem Queue Decomposition (TQD) We show that the TQD policy solves the problem of secure and efficient packet routing for a broad class of traffic, including unicast, broadcast, multicast, and anycast.
  arXiv  Detail & Related papers  (2021-09-16T12:29:41Z)
• Optimized Quantum Networks [68.8204255655161]
  Quantum networks offer the possibility to generate different kinds of entanglement prior to network requests. We utilize this to design entanglement-based quantum networks tailored to their desired functionality.
  arXiv  Detail & Related papers  (2021-07-21T18:00:07Z)
• Caching Placement and Resource Allocation for Cache-Enabling UAV NOMA Networks [87.6031308969681]
  This article investigates the cache-enabling unmanned aerial vehicle (UAV) cellular networks with massive access capability supported by non-orthogonal multiple access (NOMA) We formulate the long-term caching placement and resource allocation optimization problem for content delivery delay minimization as a Markov decision process (MDP) We propose a Q-learning based caching placement and resource allocation algorithm, where the UAV learns and selects action with emphsoft $varepsilon$-greedy strategy to search for the optimal match between actions and states.
  arXiv  Detail & Related papers  (2020-08-12T08:33:51Z)
• Neural Parameter Allocation Search [57.190693718951316]
  Training neural networks requires increasing amounts of memory. Existing methods assume networks have many identical layers and utilize hand-crafted sharing strategies that fail to generalize. We introduce Neural Allocation Search (NPAS), a novel task where the goal is to train a neural network given an arbitrary, fixed parameter budget. NPAS covers both low-budget regimes, which produce compact networks, as well as a novel high-budget regime, where additional capacity can be added to boost performance without increasing inference FLOPs.
  arXiv  Detail & Related papers  (2020-06-18T15:01:00Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.