QNUS: Reducing Terminal Resources in Quantum Secure Direct Communication Network Using Switches

Quantum secure direct communication (QSDC) offers a practical way to realize a quantum network which can transmit information securely and reliably. Practical quantum networks are hindered by the unavailability of quantum relays. To overcome this limitation, a proposal has been made to transmit the messages encrypted with classical cryptography, such as post-quantum algorithms, between intermediate nodes of the network, where encrypted messages in quantum states are read out in classical bits, and sent to the next node using QSDC. In this paper, we report a real-time demonstration of a computationally secure relay for a quantum secure direct communication network. We have chosen CRYSTALS-KYBER which has been standardized by the National Institute of Standards and Technology to encrypt the messages for transmission of the QSDC system. The quantum bit error rate of the relay system is typically below the security threshold. Our relay can support a QSDC communication rate of 2.5 kb/s within a 4 ms time delay. The experimental demonstration shows the feasibility of constructing a large-scale quantum network in the near future.

Quantum secure direct communication network with Einstein–Podolsky–Rosen pairs

As an extension of quantum key distribution, secure communication among multiple users is a basic task in a quantum network. When the quantum network structure becomes complicated with a large number of users, it is important to investigate network issues, including security, key management, latency, reliability, scalability, and cost. In this work, we utilize the classical network theory and graph theory to address two critical issues in a quantum network, security and key management. First, we design a communication scheme with the highest security level that trusts a minimum number of intermediate nodes. Second, when the quantum key is a limited resource, we design key management and data scheduling schemes to optimize the utility of data transmission. Our results can be directly applied to the current metropolitan and free-space quantum network implementations and can potentially be a standard approach for future quantum network designs.

Quantum network extends the ability to transmit information securely from two-party communication to multi-party communication with arbitrarily long distances. The efficiency of secure communication in a quantum network depends on both the topology of the network and the strategy of communication relays. In this paper, we propose a strategy to build a quantum network integrating various types of quantum secure direct communication (QSDC) schemes. A cost optimization model is presented to measure the cost of transmitting secure messages in a quantum network. Within the model, two types of quantum network strategies, the quantum circuit switching strategy and the quantum packet switching strategy, are proposed and compared. Numerical simulations in a specific network show that the quantum packet switching strategy is more favorable in future quantum networks taking into account robustness and cost required when using different types of QSDC schemes.

Teleporting energy to remote locations is new challenge for quantum information science and technology. Developing a method for transferring local energy in laboratory systems to remote locations will enable non‐trivial energy flows in quantum networks. From the perspective of quantum information engineering, we propose a method for distributing local energy to a large number of remote nodes using hyperbolic geometry. Hyperbolic networks are suitable for energy allocation in large quantum networks since the number of nodes grows exponentially. To realise long‐range quantum energy teleportation (QET), we propose a hybrid method of quantum state telepotation and QET. By transmitting local quantum information through quantum teleportation and performing conditional operations on that information, QET can theoretically be realized independent of geographical distance. The method we present will provide new insights into new applications of future large‐scale quantum networks and potential applications of quantum physics to information engineering.

The routing of vehicles or personnel in complex logistics systems is a task that needs to be solved in numerous applications, e.g., detailed models of transport networks or order picking areas. The number of relevant nodes in such networks can easily exceed 10,000 nodes. Often, a basic task is finding the shortest path from one node (start) to another (destination). Within the last years various simulation tools have been extended by respective algorithms. However, the execution time of the simulation model may significantly depend on the number of nodes in the network. We present algorithms from the literature and a comparison of three simulation tools with respect to execution time and model size for different scenarios. We further present an approach to work with so called sub-networks, i.e., the network is separated into areas, where finding the shortest path includes the task of starting at a node in one sub-network with a destination in another one.

Two experiments show that non-classical correlations can be distributed between distant nodes of a quantum network in a deterministic way. The work smooths the path for extended quantum networks. Two experiments show that non-classical correlations can be distributed between distant nodes of a quantum network in a deterministic way. The work smooths the path for extended quantum networks.

The Quantum Internet (QI) is a hypothetical global network infrastructure that exploits quantum mechanics principles to distribute qubits worldwide. The QI will enable breakthrough applications like unconditional security, distributed quantum computing, and quantum metrology. Nonetheless, the QI is currently a research-stage technology with daunting challenges until fully-functional quantum networks (QNs) can be realized. QNs are not standalone but require classical networks to assist the qubits exchange between remote places through quantum teleportation. On the other hand, QNs control and management planes will remain classical due to quantum networking technology manufacturing complexity and cost. This article addresses integrating QNs with Sixth Generation and Beyond (6GB) mobile networks. Sixth Generation and Beyond (6GB) are the foreseen next generations of wireless networks, offering extensive ubiquity and improved ultra-reliable low-latency support over larger distances than their predecessors. Therefore, it is the best-suited candidate to enable potential mobile and non-terrestrial quantum applications. Unlike existing literature highlighting quantum technology’s potential benefits to mobile networks, this work presents a fresh vision in which 6GB enhances the QI and even contributes to accelerating its development. To that end, we identify target QNs scenarios enabled, facilitated, or benefited by 6GB. We propose a Software-Defined programmable 6GB-integrated QN architecture with slicing support and the associated procedure to create virtual QNs or slices. Last, we present a proof-of-principle showing that QNs can impose deterministic low-latency requirements out of 5G reach.

We study the scaling capacity of wireless sensor networks in case of multiple gateways are presented. In such a heterogeneous network, many gateways are needed to gather data from the sensor nodes in network. Different from the previously studied single-gateway model, our proposed gateway access model allows multiple gateway nodes being seamlessly connected with high speed wire-line or wide-band radios. Once the data from the sensor node is sent to any gateway node, it can be collaboratively sent to the appropriate sink node among multiple gateways, which could effectively avoid throughput reduction due to multi-hop routing among the sensor node. This mechanism is called ``Destination-hub", which could ensure the bounded time delay and network capacity. However under such a cooperative scheme, two research issues need to be tackled. One is the number of nodes in network and the second is the scaling capacity for each node when multiple gateway nodes are presented. Our proposed model is a fundamental research work for scaling capacity, which could also provide an instructive proposal for future gateway deployment. In this paper, we characterize the scaling capacity between gateways and sensor nodes under different gateway access model. If gateway nodes are randomly deployed, the number is Omega(log n), and there are at least 4 log l gateway nodes are needed in each squarelet region so as to keep the gateway connectivity, where r is the transmitting range of sensor nodes, and l is the side length of the deployed square region. And we can conclude that, the gateway nodes can be tightly bounded by Theta(log n). For random placement, the scaling capacity for such a scheme is (n). And we have also proposed an optimized scheme for reducing the number of gateway nodes. Considering the interference Voronoi cell, the reduced gateway nodes can be 2 lnl, and still bounded by Theta(log n).

Quantum networks, which enable the transfer of quantum information across long distances, promise to provide exciting benefits and new possibilities in many areas including communication, computation, security, and metrology. These networks rely on entanglement between qubits at distant nodes to transmit information; however, creation of these quantum links is not dependent on the information to be transmitted. Researchers have explored schemes for continuous generation of entanglement, where network nodes may generate entanglement links before receiving user requests. In this paper we present an adaptive scheme that uses information from previous requests to better guide the choice of randomly generated quantum links before future requests are received. We analyze parameter spaces where such a scheme may provide benefit and observe an increase in performance of up to 75% over other continuous schemes on single-bottleneck and autonomous systems networks. We also test the scheme for other parameter choices and observe continued benefits of up to 95%. The power of our adaptive scheme on a randomized request queue is demonstrated on a single-bottleneck topology. We also explore quantum memory allocation scenarios, where a difference in latency performance implies the necessity of optimal allocation of resources for quantum networks.

Parallel Optical Burst Switching (POBS) is a variant of Optical Burst Switching (OBS) which is proposed as a new optical switching strategy for Ultra-Dense Wavelength Division Multiplexing (U-DWDM) to support the enormous bandwidth demand of the next generation Internet. As opposed to OBS, POBS transmits bursts in two dimensions: the wavelength dimension and the time dimension. POBS network uses an one-way resource reservation mechanism to set up the resources for each data burst transmission. The use of this mechanism may cause bursts to contend for the same resources at the same time at core (intermediate) nodes of the network. Therefore, the performance of POBS networks depends on the contention resolution policies to reach acceptable levels for bandwidth usage. These policies may increase both the cost and complexities of the core nodes in POBS networks. Most literatures on OBS networks apply contention resolution at the core nodes based on reactive strategies that are activated after contention takes place in core nodes. This study proposes the use of a proactive contention resolution technique at ingress nodes of POBS network as well as reactive contention resolution technique at core nodes for reducing the probability of burst drop in the network in order to increase the performance of the network. The simulation results show that the use of POBS network with the proposed Reactive Odd/Even Node ID Wavelength Assignment Technique (POBS-ROENIDWAT) shows a better performance in terms of reduced data loss rate and increased throughput compared to the performances of both POBS network with Sequential Wavelength Assignment Technique (POBS-SWAT) and OBS network with Burst Segmentation (OBS-BS).

With the deep integration of communication technology and Internet of Things technology, the edge network structure is becoming increasingly dense and heterogeneous. At the same time, in the edge network environment, characteristics such as wide-area differentiated services, decentralized deployment of computing and network resources, and highly dynamic network environment lead to the deployment of redundant or insufficient edge cache nodes, which restricts the efficiency of network service caching and resource allocation. In response to the above problems, research on the joint optimization of service caching and resources in the decentralized edge network scenario is carried out. Therefore, we have conducted research on the collaborative caching of training data among multiple edge nodes and optimized the number of collaborative caching nodes. Firstly, we use a multi-queue model to model the collaborative caching process. This model can be used to simulate the in-network cache replacement process on collaborative caching nodes. In this way, we can describe the data flow and storage changes during the caching process more clearly. Secondly, considering the limitation of storage space of edge nodes and the demand for training data within a training epoch, we propose a stochastic gradient descent algorithm to obtain the optimal number of caching nodes. This algorithm entirely takes into account the resource constraints in practical applications and provides an effective way to optimize the number of caching nodes. Finally, the simulation results clearly show that the optimized number of caching nodes can significantly improve the adequacy rate and hit rate of the training data, with the adequacy rate reaching 84% and the hit rate reaching 100%.

Quantum communications have progressed significantly, moving from a theoretical concept to small-scale experiments to recent metropolitan-scale demonstrations. As the technology matures, it is expected to revolutionize quantum computing in much the same way that classical networks revolutionized classical computing. Quantum communications will also enable breakthroughs in quantum sensing, metrology, and other areas. However, scalability has emerged as a major challenge, particularly in terms of the number and heterogeneity of nodes, the distances between nodes, the diversity of applications, and the scale of user demand. This paper describes InterQnet, a multidisciplinary project that advances scalable quantum communications through a comprehensive approach that improves devices, error handling, and network architecture. InterQnet has a two-pronged strategy to address scalability challenges: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">InterQnet-Achieve</i> focuses on practical realizations of heterogeneous quantum networks by building and then integrating first-generation quantum repeaters with error mitigation schemes and centralized automated network control systems. The resulting system will enable quantum communications between two heterogeneous quantum platforms through a third type of platform operating as a repeater node. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">InterQnet-Scale</i> focuses on a systems study of architectural choices for scalable quantum networks by developing forward-looking models of quantum network devices, advanced error correction schemes, and entanglement protocols. Here we report our current progress toward achieving our scalability goals.

In distributed networks, some groups of nodes may have more inter-connections, perhaps due to their larger bandwidth availability or communication requirements. In many scenarios, it may be useful for the nodes to know if they form part of a dense subgraph, e.g., such a dense subgraph could form a high bandwidth backbone for the network. In this work, we address the problem of self-awareness of nodes in a dynamic network with regards to graph density, i.e., we give distributed algorithms for maintaining dense subgraphs (subgraphs that the member nodes are aware of). The only knowledge that the nodes need is that of the dynamic diameter D, i.e., the maximum number of rounds it takes for a message to traverse the dynamic network. For our work, we consider a model where the number of nodes are fixed, but a powerful adversary can add or remove a limited number of edges from the network at each time step. The communication is by broadcast only and follows the CONGEST model in the sense that only messages of O(log n) size are permitted, where n is the number of nodes in the network. Our algorithms are continuously executed on the network, and at any time (after some initialization) each node will be aware if it is part (or not) of a particular dense subgraph. We give algorithms that approximate both the densest subgraph, i.e., the subgraph of the highest density in the network, and the at-least-k-densest subgraph (for a given parameter k), i.e., the densest subgraph of size at least k. We give a (2 + e)-approximation algorithm for the densest subgraph problem. The at-least-k-densest subgraph is known to be NP-hard for the general case in the centralized setting and the best known algorithm gives a 2-approximation. We present an algorithm that maintains a (3+e)-approximation in our distributed, dynamic setting. Our algorithms run in O(Dlog1+e n) time.

The quantum internet is one of the frontiers of quantum information science. It will revolutionize the way we communicate and do other tasks, and it will allow for tasks that are not possible using the current, classical internet. The backbone of a quantum internet is entanglement distributed globally in order to allow for such novel applications to be performed over long distances. Experimental progress is currently being made to realize quantum networks on a small scale, but much theoretical work is still needed in order to understand how best to distribute entanglement and to guide the realization of large-scale quantum networks, and eventually the quantum internet, especially with the limitations of near-term quantum technologies. This work provides an initial step towards this goal. The main contribution of this thesis is a mathematical framework for entanglement distribution protocols in a quantum network, which allows for discovering optimal protocols using reinforcement learning. We start with a general development of quantum decision processes, which is the theoretical backdrop of reinforcement learning. Then, we define the general task of entanglement distribution in a quantum network, and we present ground- and satellite-based quantum network architectures that incorporate practical aspects of entanglement distribution. We combine the theory of decision processes and the practical quantum network architectures into an overall entanglement distribution protocol. We also define practical figures of merit to evaluate entanglement distribution protocols, which help to guide experimental implementations.