Nour Dehaini | Searcharxiv

arXiv2026

Q-Backbone: A Quantum-Enhanced Control Plane for Future Communication Networks

Future networks will need to make network-wide decisions, including traffic engineering, network slicing, and wireless optimization, under strict latency, energy, and reliability constraints. The computational complexity of these problems increasingly challenges classical optimization methods. This article proposes Q-Backbone (QB), a quantum-enhanced control plane for communication networks in which quantum processing units (QPUs) operate alongside classical computing resources as accelerators for network intelligence. QB is designed as a fourlayer architecture that combines heterogeneous infrastructure, hybrid quantum-classical runtime services, policy-driven task orchestration, and communication-network applications. A central component of QB is the Quantum Invocation Policy (QIP), which dynamically determines when quantum acceleration is beneficial and when classical execution should be preferred. A case study on deadline-aware orchestration of distributed quantum jobs over heterogeneous QPUs shows that QB can improve workload execution under tight deadline constraints, serving up to 25% more jobs than existing quantum-cloud scheduling baselines. Finally, open challenges and opportunities towards the deployment of QB are highlighted and discussed.

cs.OH↗

arXiv2025

Deadline-Aware Scheduling of Distributed Quantum Circuits in Near-Term Quantum Cloud

Distributed quantum computing (DQC) enables scalable quantum computations by distributing large quantum circuits on multiple quantum processing units (QPUs) in the quantum cloud. In DQC, after partitioning quantum circuits, they must be scheduled and executed on heterogenous QPUs while balancing latency, overhead, QPU communication resource limits. However, since fully functioning quantum communication networks have not been realized yet, near-term quantum clouds will only rely on local operations and classical communication settings between QPUs, without entangled quantum links. Additionally, existing DQC scheduling frameworks do not account for user-defined execution deadlines and adopt inefficient wire cutting techniques. Accordingly, in this work, a deadline aware DQC scheduling framework with efficient wire cutting for near-term quantum cloud is proposed. The proposed framework schedules partitioned quantum subcircuits while accounting for circuit deadlines and QPU capacity limits. It also captures dependencies between partitioned subcircuits and distributes the execution of the sampling shots on different QPUs to have efficient wire cutting and faster execution. In this regard, a deadline-aware circuit scheduling optimization problem is formulated, and solved using simulated annealing. Simulation results show a marked improvement over existing shot-agnostic frameworks under urgent deadlines, reaching a 12.8% increase in requests served before their deadlines. Additionally, the proposed framework serves 8.16% more requests, on average, compared to state-of-the-art dependency-agnostic baseline frameworks, and by 9.60% versus the dependency-and-shot-agnostic baseline, all while achieving a smaller makespan of the DQC execution. Moreover, the proposed framework serves 23.7%, 24.5%, and 25.38% more requests compared to greedy, list scheduling, and random schedulers, respectively.

quant-ph↗