Most quantum network schemes delay entanglement generation until a request arrives, causing slower processing. To this end, an approach of pre-establishing an initial shared state has emerged. However, the initial shared state must be versatile enough to accommodate all possible requests and may consume considerable qubits. It is crucial to minimize the number of qubits used while satisfying every possible request. We first introduce a 2 -approximation algorithm for the special case where each request consists of only one Bell or GHZ state requirement. Afterward, the 2 -approximation algorithm is extended to handle any possible request that may contain one or more requirements. Finally, via extensive simulation results, we show that our algorithm can outperform existing approaches by up to 29% in used qubits.

Quantum teleportation enables high-security communications via quantum entanglement. However, decoherence, signal decay, and environmental interference may cause imperfect entangled pairs with low fidelity. Such entangled pairs may easily generate errors when used to teleport data qubits and cause fatal computation errors on quantum computers. Fortunately, data qubits can be encoded via quantum error correction (QEC) code to recover the detected error to some extent. Nevertheless, letting any repeaters process data qubits is dangerous because malicious repeaters may peep at, destroy, or fake the data qubits. Thus, in this paper, we propose a novel QEC-enabled routing framework MOON facilitated with the concept of social networks (SNs) for quantum networks (QNs). MOON selects only trusted repeaters to process data qubits and exhibits elastic routing with QEC to maximize the throughput without errors. Last, simulation results show that our framework can outperform existing approaches by up to 34% on network throughput without errors.

Entangled pairs serve as the cornerstone for secure data transmission. All-optical-switching technology on nodes enables the entangling signals to bypass nodes and build ultra-long entangled pairs. Nevertheless, entangled pairs suffer from decoherence over distance, causing inadequate fidelity and potentially compromising transmission quality. To address the challenges, we employ entanglement purification to enhance fidelity to meet the threshold. However, the purification process consumes additional entangled pairs and may fail. Besides, the purification efficiency would be poor if the input pairs have low fidelity. Thus, it is unavoidable to divide the path into sub-paths with appropriate lengths for better purification efficiency and then merge them into a longer entangled pair by swapping. The novel optimization problem DOSP then emerges: maximizing the probability while adhering to fidelity constraints. To tackle the DOSP efficiently, we propose a (1–δ)-approximation algorithm NSPS to consider the probability and fidelity jointly, where is a positive user-defined constant. Finally, the simulation results manifest that the NSPS can outperform the existing methods by at least 70%.

Traditional end-to-end entanglement typically operates between two parties. However, such a setup may fall short when three parties are involved. GHZ states, a multi-qubit entangled state, provide an approach to such a problem. A fusion node is first chosen, and then the paths from all end nodes to the fusion node are fused to create an entangled state between all parties. The selection of the fusion node becomes critical since it highly affects the success probability of the whole process. Thus, in this paper, we explore the promising scenario for multiple requests of authorizable tripartite teleportation and introduce a novel optimization problem to maximize the (expected) total profit for 3-GHZ requests. Via extensive simulation results, we show that our algorithm can outperform existing approaches significantly.

The conventional quantum teleportation schemes enable high-security network communications by establishing end-to-end entangled paths. However, those schemes focus on time synchronization and thus cause lots of idle time. Recent research suggests adopting an opportunistic scheme to forward data qubits as far as it can. However, this scheme lacks security since data qubits may be stored at malicious repeaters, which may peek at, destroy, or fake the data qubits. To this end, we design a new scheme called SOAR that considers trusted repeaters via social networks. Moreover, SOAR promotes the parallelism of swapping processes and thus leads to a less idle time of network resources than the other existing schemes. Furthermore, we design an algorithm called SAGE that can best fit SOAR by linking multiple subpaths via appropriate trusted repeaters to get an ideal path and augmenting least-hop paths to utilize the resources in quantum networks better. Simulation results manifest that SOAR outperforms the other schemes by 54%-89%; SAGE outperforms the other routing algorithms by 50% on average on SOAR.

Quantum teleportation through quantum entanglement over optical fiber channels enables secure communications. However, physical obstacles such as oceans and mountains may block optical fiber channels, and thus quantum networks (QNs) may have multiple disjoint domains. To overcome the issue, in this paper, we first propose a promising framework termed SSR to leverage satellite-based Free-Space Optical (FSO) channels to create inter-domain entangled paths for long-distance requests. Still, FSO channels may be intermittent due to satellite sparsity and atmospheric turbulence. Then, we introduce two algorithms, named RAIN and IDOL, to efficiently utilize FSO channels in SSR. RAIN estimates the existence probability of FSO channels to plan an appropriate inter-domain routing for each request while balancing domain loads. IDOL selects desired intra-domain paths and trusted repeaters for each request to teleport data qubits. Finally, simulation results manifest that SSR runs efficiently and outperforms existing approaches by 31%–57% in throughput.

Quantum teleportation via quantum entanglement enables high-security communications in networks. However, if two quantum nodes are far away, it may be difficult to create an entangled path due to the low success probability. Besides, existing approaches neglect social relations among nodes' owners. In this paper, we propose a new framework SEER to minimize the waiting time of all source-destination (SD) pairs' requests. SEER has two promising features: 1) Social-relation Consideration. SEER makes the first attempt to select trusted owners' nodes via social networks as intermediate nodes for requests to temporarily store data qubits to increase the success probability. 2) Starvation Mitigation. SEER divides long SD pairs and slices resources reasonably to remedy starvation due to their low success probability. To this end, we design RATE and PLAN to find the proper intermediate nodes and reduce the average waiting time. Simulation results manifest SEER outperforms others by 37%.