Utility-Cost Ratio Maximization in Quantum Networks for Secure Quantum Key Distribution

Abstract

In this paper, we study the utility-cost ratio (UCR) maximization problem in quantum networks, with a particular focus on secure quantum key distribution (QKD). We propose the Quantum Utility-Cost Optimization (QUCO) algorithm to address the challenge of balancing network utility with operational and infrastructure costs. The utility of the network is measured based on the secret key fraction, a key performance metric in QKD, while the costs considered include operational and maintenance expenses, transceiver deployment, auxiliary equipment, and wavelength channel usage. The QUCO algorithm transforms the original non-convex problem into a convex optimization through a series of transformations, enabling efficient resource allocation across quantum network routes. Our simulation results, conducted on a realistic quantum network topology, demonstrate the algorithm’s ability to improve the utility-cost ratio while maintaining high network performance. The QUCO algorithm strikes a balance between minimizing costs and maintaining high end-to-end entanglement fidelity, which is effective for optimizing UCR in quantum networks.