Telemetry-Based Server Selection in the Quantum Internet via Cross-Layer Runtime Estimation
Masaki Nagai, Hideaki Kawaguchi, Shin Nishio, Takahiko Satoh

TL;DR
This paper introduces $T_{max}$, a lightweight, cross-layer telemetry-based score for effective server selection in the Quantum Internet, demonstrating near-optimal performance in simulations and providing deployment insights.
Contribution
The paper proposes $T_{max}$, a novel runtime score that efficiently combines multi-layer telemetry for server selection without calibration, validated through extensive simulations.
Findings
$T_{max}$ achieves below 10% mean regret in simulations.
Performance remains robust under classical communication jitter for multi-shot jobs.
Deployment maps and sensitivity analysis offer practical guidance for Quantum Internet provisioning.
Abstract
The Quantum Internet will allow clients to delegate quantum workloads to remote servers over heterogeneous networks, but choosing the server that minimizes end-to-end execution time is difficult because server processing, feedforward classical communication, and entanglement distribution can overlap in protocol-dependent ways and shift the runtime bottleneck. We propose , a lightweight runtime score that sums coarse telemetry from multiple layers to obtain a conservative ranking for online server selection without calibrating weights for each deployment. Using NetSquid discrete-event simulations of a modified parameter-blind VQE (PB-VQE) workload, we evaluate on pools of 10,000 heterogeneous candidates (selecting among up to 100 per decision) across crossover and bottleneck-dominated regimes, including temporal jitter scenarios and jobs with multiple shots.…
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Taxonomy
TopicsCloud Computing and Resource Management · IoT and Edge/Fog Computing · Quantum Computing Algorithms and Architecture
