The fundamental technology for the construction of large-scale quantum networks lies in the efficient distribution of remote entanglement among quantum nodes. Entanglement routing tackles the challenge of path selection between two distant end nodes and realizes entanglement distribution through multi-hop entanglement swapping. Given the inherent probability of swapping, entanglement distribution flow always presents inevitable losses. The existing routing works adopt a parallel swapping mode, which only considers the final end-to-end distribution loss effect. This lag of failure detection and complete independence between swapping reduce distribution efficiency. We observe that the sequential swapping mode can improve this defect, but it is not thorough. Thus, in this paper, we explore the entanglement flow loss effect in the sequential entanglement swapping (Loss-SES) process in order to perceive failures earlier and save network resources. Subsequently, we introduce a novel metric to quantify path performance, namely the expected entanglement throughput (EET). Building upon EET, we propose the entanglement routing algorithm MaxEET adapted to the Loss-SES process to maximize EET. For efficient deployment, in the single-request scenario, we determine the optimal routing initiation direction by introducing a bidirectional routing mechanism. In the multi-request scenario, we design a greedy and contention-free iterative routing algorithm to exhaust resources. Based on extensive simulations, the results show the superiority of our proposed Loss-SES mode compared to other modes in terms of throughput, fairness, and utilization.
The fundamental technology for the construction of large-scale quantum networks lies in the efficient distribution of remote entanglement among quantum nodes. Entanglement routing tackles the challenge of path selection between two distant end nodes and realizes entanglement distribution through multi-hop entanglement swapping. Given the inherent probability of swapping, entanglement distribution flow always presents inevitable losses. The existing routing works adopt a parallel swapping mode, which only considers the final end-to-end distribution loss effect. This lag of failure detection and complete independence between swapping reduce distribution efficiency. We observe that the sequential swapping mode can improve this defect, but it is not thorough. Thus, in this paper, we explore the entanglement flow loss effect in the sequential entanglement swapping (Loss-SES) process in order to perceive failures earlier and save network resources. Subsequently, we introduce a novel metric to quantify path performance, namely the expected entanglement throughput (EET). Building upon EET, we propose the entanglement routing algorithm MaxEET adapted to the Loss-SES process to maximize EET. For efficient deployment, in the single-request scenario, we determine the optimal routing initiation direction by introducing a bidirectional routing mechanism. In the multi-request scenario, we design a greedy and contention-free iterative routing algorithm to exhaust resources. Based on extensive simulations, the results show the superiority of our proposed Loss-SES mode compared to other modes in terms of throughput, fairness, and utilization.
Entanglement distribution between distant quantum nodes plays an important role in quantum networks. However, due to the unique properties of quantum mechanics and hardware limitations, entanglement resources in quantum networks are scarce. Quantum links that fail to meet request demands become bottleneck links, significantly hindering remote entanglement distribution in multi-request scenarios. In this paper, we propose an entanglement routing scheme called SwappingBoost that can effectively reduce resource consumption along entanglement distribution paths, alleviating the negative impact of bottleneck links. SwappingBoost first employs a decreasing resource reservation method to compensate for resource losses caused by failed entanglement swapping, freeing up pre-reserved resources on downstream links to accommodate other paths and requests. Besides, SwappingBoost introduces a path-priority-based rounding algorithm that achieves integer-level resource allocation while ensuring balanced resource allocation. Extensive simulation results demonstrate that SwappingBoost can effectively reduce the load of bottleneck links, enhancing network throughput while maintaining fairness among multiple requests.
The quantum network is designed to connect numerous quantum nodes and support various ground-breaking quantum applications. Most of these applications require communicating parties to share entangled pairs. Therefore, entanglement routing, a technology distributing entangled pairs between distant quantum nodes, plays a vital role in realizing quantum networks’ capability. However, due to the limitation of quantum memory size and quantum decoherence, the entangled pairs shared by adjacent quantum nodes can hardly satisfy concurrent entanglement routing requests, thus leading to severe network congestion. In this paper, we propose a novel congestion mitigation (CM) scheme to tackle such bottleneck problems. The basic idea of CM is to “recycle” idle link-level entanglement resources from well-resourced links to bottleneck links utilizing a unique enabling technology of quantum networks, called entanglement swapping. CM can increase the capacity of each bottleneck link, thus overcoming resource limitations to improve resource utilization and network throughput. To complete our work, we also propose a swapping-based entanglement routing design, including path selection and resource allocation algorithms. Extensive simulations show that our design can significantly alleviate network congestion and improve the request service rate of quantum networks compared to the traditional entanglement routing designs.
Entanglement routing establishes remote entanglement connection between two arbitrary nodes, which is one of the most important functions in quantum networks. The existing routing mechanisms mainly improve the robustness and throughput facing the failure of entanglement generations, which, however, rarely include the considerations on the most important metric to evaluate the quality of connection, entanglement fidelity. To solve this problem, we propose purification-enabled entanglement routing designs to provide fidelity guarantee for multiple Source-Destination (S-D) pairs in quantum networks. In our proposal, we first consider the single S-D pair scenario and design an iterative routing algorithm, Q-PATH, to find the optimal purification decisions along the routing path with minimum entangled pair cost. Further, a low-complexity routing algorithm using an extended Dijkstra algorithm, Q-LEAP, is designed to reduce the computational complexity by using a simple but effective purification decision method. Finally, we consider the common scenario with multiple S-D pairs and design a greedy-based algorithm considering resource allocation and re-routing process for multiple routing requests. Simulation results show that the proposed algorithms not only can provide fidelity-guaranteed routing solutions, but also has superior performance in terms of throughput, fidelity of end-to-end entanglement connection, and resource utilization ratio, compared with the existing routing scheme.
Entanglement routing establishes remote entanglement connection between two arbitrary nodes, which is one of the most important functions in quantum networks. The existing routing mechanisms mainly improve the robustness and throughput facing the failure of entanglement generations, which, however, rarely include the considerations on the most important metric to evaluate the quality of connection, entanglement fidelity. To solve this problem, we propose purification-enabled entanglement routing designs to provide fidelity guarantee for multiple Source-Destination (SD) pairs in quantum networks. In our proposal, we first consider the single S-D pair scenario and design an iterative routing algorithm, Q-PATH, to find the optimal purification decisions along the routing path with minimum entangled pair cost. Further, a low-complexity routing algorithm using an extended Dijkstra algorithm, Q-LEAP, is designed to reduce the computational complexity by using a simple but effective purification decision method. Then we consider the common scenario with multiple S-D pairs and design a greedy-based algorithm considering resource allocation and rerouting process for multiple routing requests. To verify the effectiveness and superiority of the proposed algorithms, extensive simulations are conducted, and the simulation results show that the proposed algorithms not only can provide fidelity-guarantee routing solutions, but also has superior performance in terms of throughput, fidelity of end-to-end entanglement connection, and resource utilization ratio, compared with the existing routing scheme.
The core technology to construct large-scale quantum networks is to efficiently distribute remote entanglement among quantum nodes. Entanglement routing deals with the problem of discovering and selecting paths to perform the multi-hop entanglement swapping between two distant nodes. In order to succeed in end-to-end entanglement creation for a given path, entanglement distribution of all direct quantum links and Bell state measurement of all intermediate nodes along the path should be successful. Existing studies have addressed the entanglement routing problem based on path discovery algorithms considering the above characteristics and selecting the optimal path from the individual performance perspective of each path. In this article, we newly define the entanglement routing problem considering the joint-utilization between multiple paths to maximize the network resource efficiency, and present an optimal link-set configuration algorithm, named RELiC, as a solution for this. The performance of the proposed entanglement routing protocol is evaluated in small- and large-scale quantum networks through mathematical analysis and simulation study.
This paper considers the problem of finding an optimal order for entanglement swapping in a heterogeneous path of quantum repeaters so as to maximize the path throughput defined as the delivery rate of end-to-end entanglements. The primary difficulty in addressing this problem lies in the vast array of possible swapping orders for large paths and the complexity of the expected throughput, which depends on the attributes of each node and edge along the path, as well as the order of swapping. To cope with these issues, we first propose simple approximations in estimating the swapping outcome between two entanglement distributions that can run in constant time, thereby providing an efficient approach for evaluating and comparing different swapping orders, allowing us to solve the problem exactly for small paths. Second, as the number of possible orders grows exponentially with the number of repeaters in the path, we develop an efficient heuristic based on the greedy selection of nodes to sequentially perform swaps according to their swapping scores, defined as the expected number of entanglements resulting from their swaps. The scores are local but dynamic in the sense that they depend not just on the entanglement distributions available on the path but also on prior swapping decisions. Finally, we illustrate the efficiency and effectiveness of our proposed model and approach through extensive experimentation conducted using a general quantum network simulator.