Quantum network can provide end-to-end entanglements through quantum operations, supporting various quantum applications such as quantum key distribution and distributed quantum computing. However, many previous proposals for quantum networks assumed the division of quantum network into time slots and batch processing of network communication tasks, performing poorly in dynamic network scenarios and not fully utilizing network resources. This work focuses on the routing problem in entanglement quantum networks, aiming to provide more efficient end-to-end entanglement establishment for upper-layer applications. We propose an on-demand routing algorithm that dynamically adjusts the optimal path based on the current network conditions. Specifically, we consider the benefits of path width for quantum networks and propose an algorithm for finding the shortest wide path. Using this algorithm, each node establishes its own routing table. Additionally, to dynamically avoid network hotspots, we introduce the concept of traffic to reflect the busyness of nodes. Finally, using a dynamic cost calculation method as the routing metric, we select the optimal path for the current request. To evaluate the performance of the proposed quantum routing algorithm, we conducted simulation experiments on SimQN quantum simulation platform. The results show that our approach improves network throughput by 14 percent compared to existing solutions.
Quantum network can provide end-to-end entanglements through quantum operations, supporting various quantum applications such as quantum key distribution and distributed quantum computing. However, many previous proposals for quantum networks assumed the division of quantum network into time slots and batch processing of network communication tasks, performing poorly in dynamic network scenarios and not fully utilizing network resources. This work focuses on the routing problem in entanglement quantum networks, aiming to provide more efficient end-to-end entanglement establishment for upper-layer applications. We propose an on-demand routing algorithm that dynamically adjusts the optimal path based on the current network conditions. Specifically, we consider the benefits of path width for quantum networks and propose an algorithm for finding the shortest wide path. Using this algorithm, each node establishes its own routing table. Additionally, to dynamically avoid network hotspots, we introduce the concept of traffic to reflect the busyness of nodes. Finally, using a dynamic cost calculation method as the routing metric, we select the optimal path for the current request. To evaluate the performance of the proposed quantum routing algorithm, we conducted simulation experiments on SimQN quantum simulation platform. The results show that our approach improves network throughput by 14 percent compared to existing solutions.
With the enhanced security offered by quantum teleportation, quantum networks (QNs) are gradually gaining significant attention. However, previous research on QNs often exhausts all network resources to serve requests, hence overlooking the scarce resources in QN. This oversight easily leads to resource wastage and requests competing for limited resources. To address the above issues, this paper introduces a new optimization problem named EINS, which minimizes the maximum resource utilization and finds routing paths for each request through certain intermediate nodes. This design cleverly divides the routing path into segments to enhance routing path diversity. To solve the EINS, we design a novel algorithm named GOAL, which provides anO(log∣V∣)bound for constraint deviation. It efficiently and equitably distributes requests, ensuring optimal network utilization. Finally, the simulation results manifest that GOAL can outperform the existing methods by up to 99%.
Quantum Data Networks (QDNs) typically leverage teleportation to reliably send data quantum bits (called qubits) to their destinations. To teleport a data qubit from Alice to Bob, one entanglement connection between Alice and Bob needs to be established. Accordingly, we have to establish as many entanglement connections as possible with limited quantum resources in order to maximize the network throughput. Conventional methods assume a known traffic matrix and calculate the paths to establish entanglement connections in one batch using a centralized algorithm. However, these methods are not scalable in large scale QDNs since it is time consuming to optimize the entanglement paths for a batch of requests, which may result in a long time slot duration and significantly reduce the network throughput. To address this issue, we propose an Online Entanglement Routing (OER) scheme which determines the entanglement paths for each request when it arrives. In addition, OER pursues work conservation and fairness among all requests in the QDNs. Through extensive simulations, we demonstrate that OER not only outperforms two representative heuristics by up to 61.27% and 52.79%, respectively, in terms of average request completion time, but also achieves a better fairness performance than these two counterparts.
This paper proposes a novel approach to quantum network routing within a dynamic topology framework. The core concept revolves around leveraging the inherent properties of quantum topology, specifically exchange operations and entanglement, to construct a reconfigurable quantum network. The proposed routing algorithm dynamically optimizes the entanglement network path in real-time, aiming to achieve efficient quantum information transmission. The key innovation lies in the dynamic adjustment of routes, a significant challenge currently addressed in topological quantum network research. This work presents a theoretical framework and a foundational routing algorithm, laying the groundwork for future research and development in resilient and adaptable quantum communication networks. The system utilizes a network represented as (S1, S2, ..., SK), where Si represents a node in the network. The routing algorithm is defined as φ(S1, S2, ..., SK), which returns a sequence of nodes representing the optimal path. The efficiency of the routing is measured by the average path length (L) and the number of exchanges (E) required. A key element is the concept of topological entanglement, denoted as Eij, representing the entanglement between nodes i and j. The routing algorithm aims to minimize the total path length while maximizing the utilization of topological entanglement. The core algorithm can be expressed as: φ(S1, S2, ..., SK) = argminP Σj=1N Lj(P), where P is a path from S1 to SK, and Lj(P) is the path length of path P. The minimization is performed subject to constraints related to topological entanglement and network topology.
This paper investigates a novel routing mechanism for quantum information within dynamic topological networks, leveraging quantum entanglement and the inherent properties of topological networks. The core idea revolves around employing "quantum beacon" nodes, which utilize quantum entanglement to establish and maintain connections, and dynamically adjust the topology of the network to optimize quantum information routing. Traditional routing protocols rely on classical communication and shortest-path algorithms, which are inherently limited in the context of quantum information transfer due to the no-cloning theorem and the need for secure, state-preserving communication. This proposed approach bypasses these limitations by exploiting the unique characteristics of quantum networks. The system achieves dynamic routing by continuously calculating the optimal routing path based on the current network topology and quantum entanglement state, allowing for adaptability to changing conditions and improved performance. The paper details the theoretical framework, the mathematical model, and the core concepts underlying this dynamic routing strategy. We present a comprehensive analysis of the key parameters influencing the routing process and explore the potential benefits of this approach for building robust and efficient quantum communication networks.
This paper proposes a novel routing protocol for distributed networks inspired by quantum entanglement. Traditional classical routing protocols suffer from inherent bottlenecks and inefficiencies, particularly as network scales increase. This work introduces an entanglement-based routing scheme that mimics the behavior of entangled particles to achieve exponentially faster and more robust routing. The core concept involves mapping network nodes to quantum states and leveraging the correlated nature of entanglement to determine optimal paths. We formulate the routing problem as a search within a complex Hilbert space, utilizing probabilistic methods to approximate the desired quantum state. The proposed protocol introduces metrics for path evaluation based on entanglement strength and distance, resulting in a dynamic routing strategy. Simulation results demonstrate the potential for significant performance improvements compared to conventional routing algorithms, offering a fundamentally new approach to network routing. Further research will focus on optimizing the algorithm for practical implementation and exploring its application in diverse network topologies.
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.