Quantum entanglement enables quantum networks to provide end-to-end sharing of entangled particles, establishing multi-hop path-to-path connections between remote parties. Implementing entanglement distribution plays a vital role in increasing the network scale, and practical entanglement algorithms are required to provide end-to-end multi-hop quantum entanglement. We consider the real-time entanglement distribution (R-TED) and pre-established entanglement distribution (P-EED) to meet this requirement. Based on these two types of entanglement distribution, we propose two algorithms, i.e., R-TED-based routing and entangled pairs allocation (REA) algorithm as well as P-EED-based REA algorithm for end-to-end entanglement establishment, where the practical physical factors (e.g., finite storage capacity and limited storage time) are considered. The R-TED-based REA algorithm can orchestrate the nodes in a route and perform entanglement swapping by adopting real-time entanglement. For the P-EED-based REA algorithm, remote entangled particle sharing can be achieved via pre-shared entanglement distribution and hop-by-hop entanglement swapping. This way, the entanglement routing selection satisfies the storage time constraint and allows two far-apart nodes to share long-distance entangled particles with limited memory cells. We evaluate the performance of the proposed algorithms under different network topologies and sizes, based on which we demonstrate that the network size can significantly affect the efficiency advantage achieved by the P-EED-based approach over the R-TED-based approach.

With the continual growth in user communication needs, classical optical communications are facing developmental bottlenecks. On one hand, the communication capacity of available optical fiber resources is approaching its upper limit. On the other hand, emerging quantum computing technology poses security threats. Quantum key distribution (QKD), as a representative quantum cryptography technology, is being introduced into existing optical infrastructure to mitigate security threats. It also has pioneering application value for next-generation quantum information networks. However, limited optical fiber resources struggle to support the introduction of quantum communication over classical optical networks. There are also incompatible noise factors between the two communication paradigms. This paper proposes transitioning from unilateral adaptive routing and wavelength assignment (ARW A) to bilateral synergistic RW A (SRW A) to facilitate the coexistence of two heterogeneous communication paradigms in optical networks. Simulations have proven SRW A can increase end-to-end key supply rates from bit/s to kbit/s levels. It has an enabling effect on QKD over classical optical networks.

In the sixth-generation fixed network (F6G), network security becomes an important topic. Encryption is an effective method to prevent network attacks and realize network security. Quantum key distribution (QKD) is a promising technology to effectively address the challenge by providing secret keys due to the laws of quantum physics. New services such as high immersion experience and holographic have the characteristics of time-varying bandwidth and requirements. The introduction of optical service unit (OSU) technology makes it possible to provide the exact bandwidth used by the service. In optical transport networks, a lightpath needs to be established before service transmission, and will be removed after service transmission. Signaling is used for lightpath establishment, removal, and bandwidth adjustment. Data information transmitted in data layer and signaling information transmitted in control layer are highly vulnerable to cyberattacks, such as eavesdropping. The supply of bandwidth and key resources need to be optimized to achieve secure and stable service transmission in optical networks. Hence, how to realize bandwidth and key on demand (BKoD) provisioning for dynamic services is a key problem. To improve the flexibility of bandwidth and key resource allocation and utilization, a QKD-secured OSU-based optical transport network can be deployed. In this paper, a novel QKD-secured OSU-based optical transport network architecture is proposed and a service aware dynamic resource provisioning (SADRP) algorithm is proposed to realize BKoD. The proposed architecture uses the QKD technique to provide keys for both signaling information and data information for the first time. The proposed algorithm supplies resources according to the dynamic demand of bandwidth and key, so as to achieve the balance between dynamic demand and static resource utilization. Simulations results show that compared with the benchmark algorithm, the SADRP algorithm reduces blocking probability by 4.16%, reduces bandwidth resource utilization rate by 4.39%, reduces key resource utilization rate by 3.48%, and improves security rate by 4.17%.

Sparse Matrix-Vector Multiplication (SpMV) is a fundamental operation in a number of scientific and engineering problems. When the sparse matrices processed are large enough, distributed memory systems should be used to accelerate SpMV. At present, the optimization techniques for distributed SpMV mainly focus on reordering through graph or hypergraph partitioning. However, although the reordering could reduce the amount of communications in general, there are still load balancing challenges in computations and communications on distributed platforms that are not well addressed. In this paper, we propose two strategies to optimize SpMV on distributed clusters: (1) resizing the number of row blocks on the nodes for balancing the amount of computations, and (2) adjusting the column number of the diagonal blocks for balancing tasks and reducing communications among compute nodes. The experimental results show that compared with the classic distributed SpMV implementation and its variant reordered with graph partitioning, our algorithm achieves on average 77.20x and 5.18x (up to 460.52x and 27.50x) speedups, respectively. Also, our method bring on average 19.56x (up to 48.49x) speedup over a recently proposed hybrid distributed SpMV algorithm. In addition, our algorithm achieves obviously better scalability over these existing distributed SpMV methods.

Datacenter networks (DCNs) with cloud–edge collaboration are emerging to satisfy the communication, computation, and caching (3C) requirements of future services such as cloud-based IoT services. However, the enroute data over DCNs with cloud–edge collaboration is likely to suffer from cyberattacks such as eavesdropping. A large number of services require not only 3C resources, but also cryptographic resources for encryption to ensure high security. Quantum key distribution (QKD) is a practical approach to provide secret keys for remote users with information-theoretic security against attacks from quantum computing. A QKD-secured DCN (QKD-DCN) with cloud–edge collaboration can be deployed to satisfy the communication, computation, caching, and cryptographic (4C) requirements of services. This article innovatively solves the new 4C resource-allocation (4CRA) problem in the network to minimize the cryptographic resource consumption. It formulates an integer linear programming (ILP) model and proposes a heuristic cryptographic-dependent 4CRA algorithm to find optimal solutions. The proposed algorithm is compared with two baseline 4CRA algorithms which, respectively, consider the minimized service delivery latency and the first-fit resource availability. Analytical simulations show that the proposed algorithm minimizes the key-resource-consumption ratio and the average key-resource consumption under static and dynamic traffic scenarios in different network topologies.

With the advent of smart homes, smart cities, and smart everything, the Internet of Things (IoT) has emerged as an area of incredible impact, potential, and growth. Internet of Things date security remain a major challenge, in the current Internet of Things systems, a relatively easy method of data encryption is used to ensure the security of data transmission, which is commonly called lightweight cryptography. However, such method is at the risk of being cracked by quantum computers, which will contribute to many challenges specially related to privacy and security in IoT. As a result, the architecture of IoT needs to be re-designed considering the security challenges brought by quantum computers. On the other hand, Quantum Key Distribution (QKD) allows two users to share unconditionally secure keys. Unlike classical cryptosystems, the security of QKD is based on the fundamentals of quantum mechanics. This security of QKD is independent of computational complexity and will not be affected, no matter how much computing power the adversary has. This paper introduces a quantum key distribution enhanced Internet of Things architecture and proposes a residual-adaptive key provisioning scheme, which is evaluated in terms of key distribution success rate in the simulation.

Free-space long-distance quantum key distribution (QKD) has the characteristics of low attenuation and wide coverage, which can overcome the limitation of transmission distance based on ground optical fiber QKD networks. Long-distance QKD requests can be relayed by quantum satellites to achieve intercontinental QKD. At present, there is only one quantum satellite in space, quantum satellite network with multiple quantum satellites is necessary to be deployed to cover the global. Thus, how to construct the quantum satellite network becomes a new challenge. In this paper, we propose a centralized and distributed collaborative scheme of quantum satellite network. Low-Earth-orbit (LEO) quantum satellites, as important relay satellites, will affect the performance of the global QKD network. Based on the above architecture, we analyze the influence of the structure of LEO quantum satellite constellation on the QKD performance. Simulation results show that the key relay performance of the constellation is related to the form of inter-satellite link. and the more the number of satellites is, the greater the successful probability of the key relay services will be.

Traffic flows are often processed by a chain of Service Functions (SFs) (known as Service Function Chaining (SFC)) to satisfy service requirements. The deployed path for a SFC is called Service Function Path (SFP). SFs can be virtualized and migrated to datacenters, thanks to the evolution of Software Defined Network (SDN) and Network Function Virtualization (NFV). In such a scenario, provisioning of paths (i.e., SFPs) between virtualized network functions is an important problem. SFP provisioning becomes more complex in a multi-domain network topology. `Topology aggregation' helps to create a single-domain view of such a network by abstracting multi-domain networks. However, traditional `topology aggregation' methods are unable to abstract SF resources properly, which is required for SFP provisioning. In this paper, we propose an SFC-Oriented Topology Aggregation (SOTA) method to enable abstraction for SFs in multi-domain optical networks. This study explores the node and the link aggregation degree to evaluate information compression during the `Topology aggregation' process. Additionally, we also propose a new data structure named wheel matrix and related operations to store routing information in the aggregated topology. Based on SOTA, we propose two cross-domain SFP provisioning algorithms named Ordered Anchor Selection (OAS) and ${k}$ -paths OAS (K-OAS), and a benchmark named Global OAS (GOAS). Simulation results show that SOTA could aggregate large-scale multi-domain optical networks into a small network that contains only 6.9% of the nodes and 10.1% of the links. Both OAS and K-OAS can calculate SFPs efficiently and reduce blocking probability up to 52.10% compared to the benchmark.

We propose a multi-path fragmentation-aware routing, modulation and spectrum assignment algorithm (RMSA) for advance reservation (AR) and immediate reservation (IR) requests in elastic optical networks. To decrease fragmentation, we propose splitting requests into different parts and transferring each of these parts along a single-path or multi-paths utilizing sliceable bandwidth variable transponders. We first introduce a model to solve the problem and propose a two-dimensional fragmentation occurrence measurement in spectrum and time domains. Then we propose a multi-path fragmentation-aware RMSA algorithm (MPFA). Simulation results show that MPFA can achieve better performance than existing algorithms in terms of blocking probability and spectrum utilization.