RADAR-Q: Resource-Aware Distributed Asynchronous Routing for Entanglement Distribution in Multi-Tenant Quantum Networks

Abstract

Scalable quantum networks must support concurrent entanglement requests, yet existing routing protocols fail when users compete for shared repeater resources, wasting fragile quantum states. This paper presents RADAR-Q, a resource-aware decentralized routing protocol embedding real-time resource contention into path selection. Unlike prior designs requiring global coordination or central anchors, RADAR-Q makes intelligent local decisions balancing path length and fidelity, instantaneous quantum memory availability, and intermediate Bell-State Measurement (BSM) operations. By identifying the Nearest Common Ancestor (NCA) within a DODAG hierarchy, RADAR-Q localizes entanglement swapping close to communicating users - avoiding unnecessary central detours and reducing BSM chain length and decoherence exposure. We evaluate RADAR-Q on grid and random topologies against synchronous and root-centric asynchronous baselines. Results show RADAR-Q achieves aggregate throughputs 2.5x and 7.6x higher than synchronized and root-centric designs, respectively. While baselines suffer catastrophic fidelity collapse below the 0.5 threshold under high load, RADAR-Q consistently maintains end-to-end fidelity above 0.76, ensuring pairs remain usable. Furthermore, RADAR-Q exhibits near-perfect fairness (Jain's Fairness Index 96-98%) and retains over 50% of its ideal throughput under stringent 1.0 ms coherence times. These findings establish contention-aware decentralized routing as a scalable foundation for multi-tenant quantum networks.

Figures (6)

• Figure 1: Distributed signaling for DODAG maintenance. Neighbor discovery and rank propagation via DIS, DIO, and DAO messages in an asynchronous environment.
• Figure 2: Structural mapping from a physical grid topology (left) to the corresponding logical DODAG (right). Node colors indicate roles: cyan for user pair 1 ($s_1$, $d_1$), green for user pair 2 ($s_2$, $d_2$), blue for repeater nodes, and red for the DODAG root. Red dashed arrows show root-centric default paths; colored solid lines show RADAR-Q's NCA-optimized paths. The grid serves as an illustrative example; RADAR-Q operates on arbitrary graph topologies.
• Figure 3: Aggregate throughput scalability ($T_{co} = \infty$). RADAR-Q achieves near-linear growth, outperforming the root-centric baseline by up to 7.6$\times$ in Grid networks.
• Figure 4: End-to-end fidelity vs. request concurrency. While baseline fidelity collapses below the 0.5 threshold, RADAR-Q maintains physical usability (fidelity $\approx 0.76$) through precision trading.
• Figure 5: Jain's Fairness Index for resource allocation. RADAR-Q preserves perfect equity (Index $\approx 0.98$), preventing the structural bottlenecks that cause the 74% collapse in Asynch-Root.