Resource Allocation in Quantum-Key-Distribution Optical Data Center Networks

The paper investigates quantum key resource allocation in quantum-key-distribution optical data center networks (QKD-ODCNs). A novel framework of priority queue with multiple security levels is first proposed to achieve a multi-class networking environment with adaptive security level classification. Accordingly, a novel integer linear programming (ILP) model is developed for the quantum key resource allocation (QKRA) process. To overcome the high computation complexity in solving the ILP, two heuristic approaches are developed, namely QKRA with adaptive strong security level (QKRA-ASSL) and QKRA with adaptive weak security level (QKRA-AWSL), respectively, aiming to achieve as close performance to that by the ILP model as possible in terms of success rate of connection request and network security level. The simulation results verify that the proposed QKRA-ASSL and QKRA-AWSL approaches not only maximize the network security score, but also improve the timeslot resource utilization without compromising the establishment success rate of connection request.