Efficient Routing on Quantum Networks using Adaptive Clustering

TL;DR

QuARC is a clustering-based quantum routing protocol that adaptively reconfigures networks for high-throughput, low-overhead entanglement distribution without prior physical parameter knowledge.

Contribution

Introduces QuARC, a novel adaptive clustering-based entanglement routing protocol for quantum networks that does not require prior physical parameter knowledge.

Findings

Robust against physical network parameter changes

Maintains high throughput at scale

Prevents starvation in entanglement distribution

Abstract

We introduce QuARC, Quantum Adaptive Routing using Clusters, a novel clustering-based entanglement routing protocol that leverages redundant, multi-path routing through multi-particle projective quantum measurements to enable high-throughput, low-overhead, starvation-free entanglement distribution. At its core, QuARC periodically reconfigures the underlying quantum network into clusters of different sizes, where each cluster acts as a small network that distributes entanglement across itself, and the end-to-end entanglement is established by further distributing between clusters. QuARC does not require a-priori knowledge of any physical parameters, and is able to adapt the network configuration using static topology information, and using local (within-cluster) measurements only. We present a comprehensive simulation-based evaluation that shows QuARC is robust against changes to physical network parameters, and maintains high throughput without starvation even as network sizes scale and physical parameters degrade.