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.
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 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 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.
Quantum networks are designed to transmit quantum bits (qubits) among quantum devices to enable new network resources for the applications. Entanglement distribution and entanglement swapping are fundamental procedures that are required in several network operations. However, they are probabilistic operations, which can lead to severe network performance degradation. This article investigates the engineering problem of resource allocation in quantum networks, considering factors like entanglement distribution probability, quantum memory characteristics, and fidelity. We model this as an optimization model to obtain an optimal solution. In particular, we formulate an integer linear programming (ILP) and develop a heuristic algorithm, aiming to minimize the number of required entangled qubit pairs (Bell pairs or EPR pairs) in any adjacent pair in the quantum network. Extensive simulations are performed to compare the performance of proposed ILP and heuristic. In all the cases, the heuristic produces a comparable solution to the optimal one. Simulation results ensure that the value of maximum utilized Bell pairs in a quantum network highly depends on the value of the probability of entangled pairs established, considering the time in the quantum memory besides the number of incoming requests.
Remote entanglement distribution plays a crucial role in quantum networks, which can support many essential and exciting quantum applications. As the network scale expands, it is urgent to design a general and efficient remote entanglement distribution protocol. Nowadays, connection-oriented remote entanglement distribution protocols are available to achieve reliable entanglement distribution. However, in memory-limited quantum networks, connection-oriented entanglement distribution protocols cannot utilize entanglement resources fully and increase the delay of End-to-End (E2E) entanglement connection establishment. To overcome these shortcomings of existing entanglement distribution protocols, we design a connectionless remote entanglement distribution protocol to let Source-Destination (S-D) pairs compete for entanglement resources simultaneously. In our protocol, a fair request scheduling algorithm is proposed to reduce the waiting time without entanglement connections between S-D pairs. Furthermore, a fast scheduling trigger mechanism is proposed to perform entanglement swapping timely to reduce the delay of E2E entanglement connection establishment. The simulation results show that the designed protocol has advantages in terms of resource utilization, throughput, the service completion time of S-D pairs, and the maximum waiting time, compared with the existing remote entanglement distribution protocol.
Abstract Quantum network is a promising platform for many ground-breaking applications that lie beyond the capability of its classical counterparts. Efficient entanglement generation on quantum networks with relatively limited resources such as quantum memories is essential to fully realize the network’s capabilities, the solution to which calls for delicate network design and is currently at the primitive stage. In this study we propose an effective routing scheme to enable automatic responses for multiple requests of entanglement generation between source-terminal stations on a quantum lattice network with finite edge capacities. Multiple connection paths are exploited for each connection request while entanglement fidelity is ensured for each path by performing entanglement purification. The routing scheme is highly modularized with a flexible nature, embedding quantum operations within the algorithmic workflow, whose performance is evaluated from multiple perspectives. In particular, three algorithms are proposed and compared for the scheduling of capacity allocation on the edges of quantum network. Embodying the ideas of proportional share and progressive filling that have been well-studied in classical routing problems, we design another scheduling algorithm, the propagatory update method, which in certain aspects overrides the two algorithms based on classical heuristics in scheduling performances. The general solution scheme paves the road for effective design of efficient routing and flow control protocols on applicational quantum networks.
Quantum networks, with applications like Quantum Key Distribution (QKD), are gaining significant attention. However, their implementation faces challenges due to low entanglement generation success rates and quantum decoherence. Recent quantum technology advancements have extended entanglement memory lifetimes to one minute, termed cutoff, opening new opportunities for entanglement routing. We propose the Adaptive Entanglement Routing (AER) algorithm, which optimizes resource utilization to improve the success probability of serving entanglement and ultimately reduce the time needed for entanglement establishment. AER includes two phases: 1) determine redundant paths based on load and 2) utilize shared entanglements for entanglement swapping. Moreover, we design the highest-success-path (HSP) algorithm to maximize the success probability of entanglement routing with limited quantum memory. These innovative routing algorithms significantly reduce entanglement request failures, resulting in up to 70% reduction in average waiting times.