Route Planning and Online Routing for Quantum Key Distribution Networks

TL;DR

This paper investigates routing challenges in Quantum Key Distribution networks, proposing quadratic programming models and analyzing routing strategies to improve efficiency and fairness in both planning and online scenarios.

Contribution

It introduces a quadratic programming approach for route planning and provides theoretical analysis of routing strategies' performance in QKD networks.

Findings

Shortest path routing performs poorly online.

Widest shortest path routing has a competitive ratio ≥ 1/2.

Proposes models addressing both route planning and online routing.

Abstract

Quantum Key Distribution (QKD) networks harness the principles of quantum physics in order to securely transmit cryptographic key material, providing physical guarantees. These networks require traditional management and operational components, such as routing information through the network elements. However, due to the limitations on capacity and the particularities of information handling in these networks, traditional shortest paths algorithms for routing perform poorly on both route planning and online routing, which is counterintuitive. Moreover, due to the scarce resources in such networks, often the expressed demand cannot be met by any assignment of routes. To address both the route planning problem and the need for fair automated suggestions in infeasible cases, we propose to model this problem as a Quadratic Programming (QP) problem. For the online routing problem, we showcase that the shortest (available) paths routing strategy performs poorly in the online setting. Furthermore, we prove that the widest shortest path routing strategy has a competitive ratio greater or equal than $\frac{1}{2}$, efficiently addressing both routing modes in QKD networks.