🤖 AI Summary
Current quantum networks suffer from hardware specialization, poor scalability, and shortages of both skilled personnel and infrastructure, hindering open research and practical applications. To address these limitations, this paper introduces the first open quantum network virtualization platform designed for fair resource sharing. It cloudifies core laboratory-grade hardware—including photonic entanglement sources, time taggers, and optical switches—enabling remote coincidence counting experiments and interactive quantum resource allocation. A novel dynamic resource scheduling mechanism, based on the Hungarian algorithm, is proposed to ensure equitable and efficient distribution of entanglement rates among multiple concurrent users. Experimental evaluation confirms the platform’s functional completeness, millisecond-level response latency, and strong scalability. The platform significantly enhances accessibility to quantum networking capabilities and improves resource reuse efficiency, thereby lowering barriers to entry for quantum network experimentation and development.
📝 Abstract
The rise of quantum networks has revolutionized domains such as communication, sensing, and cybersecurity. Despite this progress, current quantum network systems remain limited in scale, are highly application-specific (e.g., for quantum key distribution), and lack a clear road map for global expansion. These limitations are largely driven by a shortage of skilled professionals, limited accessibility to quantum infrastructure, and the high complexity and cost associated with building and operating quantum hardware. To address these challenges, this paper proposes an open-access software-based quantum network virtualization platform designed to facilitate scalable and remote interaction with quantum hardware. The system is built around a cloud application that virtualizes the core hardware components of a lab-scale quantum network testbed, including the time tagger and optical switch, enabling users to perform coincidence counts of the photon entanglements while ensuring fair resource allocation. The fairness is ensured by employing the Hungarian Algorithm to allocate nearly equal effective entanglement rates among users. We provide implementation details and performance analysis from the perspectives of hardware, software, and cloud platform, which demonstrates the functionality and efficiency of the developed prototype.