Quantum networks are an actively researched and promising field, aiming to achieve efficient quantum information transmission by interconnecting quantum nodes. In large-scale quantum networks, end-to-end throughput is a critical factor that affects the overall performance of the network. The maximum flow problem, extensively studied in classical network theory, identifies a set of paths between the source and destination nodes that maximizes the total flow. This study extends the maximum flow problem to quantum networks, focusing on coordinating multiple paths for multi-path quantum communication. We propose a Quantum Multi-Path Communication Protocol (QMCP) that employs maximum flow theory to allocate transmission resources across multiple nodes efficiently, thus maximizing the total transmission capacity from the source to the destination. Our evaluation demonstrates that QMCP significantly enhances end-to-end throughput in quantum networks.
Quantum networks are an actively researched and promising field, aiming to achieve efficient quantum information transmission by interconnecting quantum nodes. In large-scale quantum networks, end-to-end throughput is a critical factor that affects the overall performance of the network. The maximum flow problem, extensively studied in classical network theory, identifies a set of paths between the source and destination nodes that maximizes the total flow. This study extends the maximum flow problem to quantum networks, focusing on coordinating multiple paths for multi-path quantum communication. We propose a Quantum Multi-Path Communication Protocol (QMCP) that employs maximum flow theory to allocate transmission resources across multiple nodes efficiently, thus maximizing the total transmission capacity from the source to the destination. Our evaluation demonstrates that QMCP significantly enhances end-to-end throughput in quantum networks.
In recent years, quantum communication networks have emerged as a promising alternative to classical communication networks for the transmission of quantum information. One of the challenges for achieving optimal performance in quantum communication networks is the efficient routing of quantum signals across multiple paths. To address this, a variety of routing protocols have been proposed, including multi-path routing protocols. Multi-path routing involves sending a quantum signal through multiple distinct paths simultaneously to reduce delays in the transmission of quantum information. By distributing the quantum information over multiple paths, this approach can provide significant performance improvements, including reduced latency and higher throughput. In addition, multi-path routing can enable new possibilities for the security of quantum communication networks, such as more secure entanglement swapping protocols and improved protection against eavesdropping. In this paper, we investigate the performance of multi-path routing protocols in multi-node quantum communication networks. We consider two approaches to multi-path routing, a basic routing approach based on shortest path optimization, and a more advanced approach based on graph partitions. We evaluate the performance of these protocols in a range of multi-node networks, with focus on the trade-off between latency and throughput. The results show that multi-path routing yields significant performance improvements in such networks and provides an efficient way for routing quantum signals across multiple paths.
This paper explores the optimization of multi-path communication within quantum networks, aiming to enhance communication efficiency and reliability. The core concept involves distributing quantum information across multiple paths and employing an optimized algorithm to manage this distribution. The algorithm focuses on minimizing latency, maximizing throughput, and mitigating the effects of channel loss inherent in quantum communication. We present a novel approach utilizing a layered optimization strategy, combining shortest path routing with adaptive power allocation. Mathematical formulations are detailed, including metrics for path quality, latency, and overall network throughput. The proposed method offers a significant improvement over traditional single-path communication strategies, particularly in complex quantum network topologies. Simulation results (though not presented through experimental data) demonstrate a substantial increase in communication performance under various network conditions. Further research will explore integration with quantum error correction codes and dynamic network topology adaptation.
We consider the problem of multi-path entanglement distribution to a pair of nodes in a quantum network consisting of devices with non-deterministic entanglement swapping capabilities. Multi-path entanglement distribution enables a network to establish end-to-end entangled links across any number of available paths with pre-established elementary (link-level) entanglement. Probabilistic entanglement swapping, on the other hand, limits the amount of entanglement that is shared between the nodes; this is especially the case when, due to architectural and other practical constraints, swaps must be performed in temporal proximity to each other. Limiting our focus to the case where only bipartite entangled states are generated across the network, we cast the problem as an instance of generalized flow maximization between two quantum end nodes wishing to communicate. We propose a mixed-integer quadratically constrained program (MIQCP) to solve this flow problem for networks with arbitrary topology. We then compute the overall network capacity, defined as the maximum number of EPR states distributed to users per time unit, by solving the flow problem for all possible network states generated by probabilistic entangled link presence and absence, and subsequently by averaging over all network state capacities. The MIQCP can also be applied to networks with multiplexed links – ie, links capable of generating multiple EPR pairs per time unit – by converting the original network state's graph into an equivalent one with unit link capacities. While our approach for computing the overall network capacity has the undesirable property that the total number of states grows exponentially with link multiplexing capability, it nevertheless yields an exact solution that serves as an upper bound comparison basis for the throughput performance of more easily-implementable yet non-optimal entanglement routing algorithms. We apply our capacity computation method to several multiplexed and non-multiplexed networks, including a topology based on SURFnet – a backbone network used for research purposes in the Netherlands – for which real fiber length data is available.
Quantum communications using entangled photons as qubits offer a promising approach to quantum key distribution, enhancing network security. However, establishing successful entanglement links between distant nodes is challenging due to factors like distance and rapid entanglement decay, resulting in low network transmission efficiency for quantum key distribution. This paper studies the problem of finding the maximum quantum communication network transmission scheme for multiple source-destination pairs with considering the success rate of quantum entangle establishments. We propose the Feasible Quantum Communication Network Transmission (fQUIET) algorithm, which leverages network transformation and auxiliary network construction. The Maximum Quantum commUnIcation nEtwork Transmission (mQUIET) algorithm is further proposed by iteratively searching for augmenting paths. Through theoretical analysis, we demonstrate that the mQUIET algorithm is capable of achieving the maximum QCN transmission scheme. Extensive experiments are carried out and the results reveal that our suggested algorithms have superior performance compared to existing methods.
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.
Due to the fact that quantum networks can provide higher security in communications, many related issues have been presented and addressed recently. One of the most important issues is to study the routing in quantum networks with multiple source-destination pairs while maximizing the total end-to-end entanglement rate. In previous studies, the shortest paths are typically selected as the entanglement paths for a source-destination pair to increase the total end-to-end entanglement rate. However, this approach is only efficient once the network resources are sufficient. Moreover, source-destination pairs only require a specific entanglement rate rather than the shortest paths. Therefore, in this paper, we suppose that each source-destination pair requires an upper bound of the entanglement rate. Under this assumption, a novel problem is proposed to construct entanglement paths for a set of multiple source-destination pairs such that the total end-to-end entanglement rate is maximized. We then propose a greedy algorithm to solve the problem. Finally, the simulation is conducted to evaluate the performance of the proposed algorithm.