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International Conference on Quantum Communications, Networking, and Computing (QCNC)

Towards QoS-Aware Quantum Networks

Ruilin Zhou, Yuhang Gan, Yi Liu, Katia Obraczka, Chen Qian

Published Jul 1, 2024• 3 citations
Publisher

Abstract

Quality of Service (QoS) has been studied in classic networks to support various applications. Due to the unique prop-erties of quantum networks, like entanglement and superposition, the definition and requirements of QoS in quantum networks differ significantly from classical networks. Limited work has been done from the application side to investigate these differences. Moreover, quantum applications exhibit distinct service requirements compared to traditional network applications, such as the need for quantum state preservation and fidelity requirements. Therefore, this work aims to analyze and model various quantum applications to identify the fundamental services required in quantum networks to provide application-specific QoS. We further propose a novel QoS routing framework, called Q2R, for quantum networks to demonstrate a possible method to achieve QoS via routing. Q2R computes feasible paths for each request and meets the fidelity and number of qubits requirements. With our framework, we can allocate resources more efficiently and our scheduling algorithm also considers fairness among different requests.

DOI
10.1109/qcnc62729.2024.00052

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Quality of Service (QoS) has been studied in classic networks to support various applications. Due to the unique prop-erties of quantum networks, like entanglement and superposition, the definition and requirements of QoS in quantum networks differ significantly from classical networks. Limited work has been done from the application side to investigate these differences. Moreover, quantum applications exhibit distinct service requirements compared to traditional network applications, such as the need for quantum state preservation and fidelity requirements. Therefore, this work aims to analyze and model various quantum applications to identify the fundamental services required in quantum networks to provide application-specific QoS. We further propose a novel QoS routing framework, called Q2R, for quantum networks to demonstrate a possible method to achieve QoS via routing. Q2R computes feasible paths for each request and meets the fidelity and number of qubits requirements. With our framework, we can allocate resources more efficiently and our scheduling algorithm also considers fairness among different requests.
Abstract Entanglement-based quantum networks require intelligent routing mechanisms that not only maximize fidelity and connectivity but also ensure service differentiation under varying traffic conditions. In this work, we propose a novel QoS-aware traffic modeling and scheduling framework integrated into a reinforcement learning-based quantum routing agent. Unlike prior approaches that assume deterministic or uniform request arrival patterns, our model introduces stochastic and bursty traffic scenarios using Erlang and ON/OFF distributions to emulate realistic quantum workloads. Each entanglement request is assigned a set of QoS attributes, including fidelity requirements, time-to-live constraints, and priority levels. We then extend the reward function of the agent to consider deadline compliance and resource efficiency in addition to fidelity. Through simulation, we compare the proposed method against state-of-the-art baselines, including DQRA and Proactive RL, under both best-effort and QoS-prioritized scheduling modes. Results demonstrate that our approach maintains higher success rates and lower latency for high-priority requests, while preserving entanglement fidelity and efficient resource allocation across varying network loads. This study highlights the importance of integrating QoS mechanisms into quantum routing to support scalable and differentiated quantum services
Future quantum networks will enable the interconnection of multiple users distributed across vast geographic distances. Due to these large separations and limited physical resources, communication will often rely on multi-path routing strategies, where physical resources are distributed across channels of varying lengths and delivered to end users. Efficient long-distance quantum communication therefore requires optimizing the allocation of these resources across available paths. In this work, we introduce a performance-oriented approach to quantum network routing by extending the classical concept of Quality of Service (QoS) to the context of multi-path quantum resources distribution. Unlike prior models that consider entanglement generation or quantum memory coherence in isolation, we investigate the interplay between path assignment strategies, coherence time constraints, and quantum error correction (QEC), and how they jointly impact end-to-end communication fidelity. We analyze both unencoded and encoded transmissions over aggregated network paths, quantifying the effects of resource allocation on transmission success. Our findings show that fidelity cannot be optimized independently of memory lifetimes, and that while QEC can enhance performance under specific conditions, it also imposes additional constraints depending on network topology and path-length asymmetries. This work provides a foundation for developing QoS-aware quantum routing protocols that balance fidelity, throughput, and memory utilization -- key considerations for near-term quantum repeater networks.
Quantum networks are essential infrastructure for enabling large-scale and long-distance quantum communications but face significant challenges in routing optimization and resource allocation due to their probabilistic nature and quantum resource limitations. Existing approaches typically tackle these problems in isolation, often by simply applying classical routing algorithms, maximizing the overall profit to allocate resources without considering fairness, or improving fairness in an ad-hoc way without a rigorous model. This paper proposes a general framework to systematically address these challenges. First, we conduct a thorough analysis of quantum network metrics using routing algebra as the mathematical foundation, and design provably optimal routing algorithms to tackle the unique challenges arising from their probabilistic characteristics. Second, we formulate an optimization model that simultaneously considers fairness among concurrent requests while respecting various quantum resource constraints, and design efficient near-optimal heuristics to solve it. The proposed framework provides both theoretical insights and practical solutions for the design and management of future quantum networks.
Quantum networks are envisioned to enable reliable distribution and manipulation of quantum information across distances, forming the foundation of a future quantum internet. The fair and efficient allocation of communication resources in such networks has been addressed through the quantum network utility maximization (QNUM) framework, which optimizes network utility under the assumption of predetermined routes for competing user demands. In this work, we relax this assumption and aim to identify optimal routes that correspond to the maximum achievable network utility. Specifically, we formulate the single-path utility-based entanglement routing problem as a Mixed-Integer Convex Program (MICP). The formulation is exact when negativity is chosen as the entanglement measure for utility quantification or the network supports sufficiently high entanglement generation rates across demands. For other entanglement measures considered, the formulation approximates the problem with over 99.99% accuracy on evaluated real-world examples. To improve computational tractability, we propose a randomized rounding-based heuristic and an upper bound via the relaxation of the MICP. Furthermore, based on min-congestion routing, we introduce an alternative randomized heuristic and upper bound. This heuristic is computationally faster, while both the heuristic and the upper bound often outperform their counterparts on considered real-world networks. Our work provides the framework for extending classical flow-based and quality of service-aware routing concepts to quantum networks.
Quantum networks are essential infrastructure for enabling large-scale and long-distance quantum communications but face significant challenges in routing optimization and resource allocation due to their probabilistic nature and quantum resource limitations. Existing approaches typically tackle these problems in isolation, often by simply applying classical routing algorithms, maximizing the overall profit to allocate resources without considering fairness, or improving fairness in an ad-hoc way without a rigorous model. This paper proposes a general framework to systematically address these challenges. First, we conduct a thorough analysis of quantum network metrics using routing algebra as the mathematical foundation, and design provably optimal routing algorithms to tackle the unique challenges arising from their probabilistic characteristics. Second, we formulate an optimization model that simultaneously considers fairness among concurrent requests while respecting various quantum resource constraints, and design efficient near-optimal heuristics to solve it. The proposed framework provides both theoretical insights and practical solutions for the design and management of future quantum networks.
Quantum networks are essential infrastructure for enabling large-scale and long-distance quantum communications but face significant challenges in routing optimization and resource allocation due to their probabilistic nature and quantum resource limitations. Existing approaches typically tackle these problems in isolation, often by simply applying classical routing algorithms, maximizing the overall profit to allocate resources without considering fairness, or improving fairness in an ad-hoc way without a rigorous model. This paper proposes a general framework to systematically address these challenges. First, we conduct a thorough analysis of quantum network metrics using routing algebra as the mathematical foundation, and design provably optimal routing algorithms to tackle the unique challenges arising from their probabilistic characteristics. Second, we formulate an optimization model that simultaneously considers fairness among concurrent requests while respecting various quantum resource constraints, and design efficient near-optimal heuristics to solve it. The proposed framework provides both theoretical insights and practical solutions for the design and management of future quantum networks.