Space-Ground Integrated Network (SGIN) is a multi-domain integrated network with a large coverage area, which can better meet the ubiquitous communication needs in the network and provide users with better services. It has become the main development direction of 6G network. The different networks integrated in SGIN are heterogeneous, which is specifically reflected in the fact that the periodic movement of satellite networks brings time-varying nature to resources, and the expansion of network scale also brings spatial attributes to resources. It can be concluded that resources in SGIN have multi-dimensional. When performing virtual network embedding(VNE) in SGIN, the existing embedding algorithms often do not consider the multi-dimensionality of resources, which may lead to problems such as spatially dispersed embedding results and inability to adapt to network dynamic changes. To address this problem, this paper uses the space-time resource tree(S-TRT) model to represent the multi-dimensional resources in SGIN, reflecting the performance of resources in four dimensions: time, space, type, and quantity. On the basis of this model, combined with multiple dimensions of resources and the spatial distribution of embedded nodes, the ranking vector of virtual nodes is established, and the dimensionality reduction sorting of each virtual node is carried out by multi-dimensional scaling method. Afterwards, the node embedding is completed by dynamically sorting the physical nodes to improve the spatial concentration of the embedding results and better adapt to the dynamic changes of the underlying network. Finally, we conducted a simulation experiment on the algorithm, and the results show that the algorithm has good performance in the request acceptance rate and long-term revenue-to-cost ratio.
Multi-domain network is a large-scale underlying network, which is connected to each other through links but independent of each other, and network virtualization methods are used for virtual network mapping in a multi-domain network environment. How to better allocate physical resources to virtual networks and ensure that the average failure rate of the network is minimized is the focus of the current network virtualization research field. Most of the existing research on multi-domain network environment aims to improve the resource utilization of the network, ignoring the generation of network fragmentation and the failure rate of nodes and links in the network, and does not consider the differences between each network domain. Based on the current research, we propose a virtual network mapping algorithm based on multilevel reliable ordering in multi-domain networks (MRS-VNE). First, we adopt a hierarchical collaborative multi-domain network mapping framework, then propose a multi-level reliable ordering of network domains and physical nodes, prioritize intra-domain virtual network mapping, and finally, adopt heuristic inter-domain virtual network mapping for VNRs that fail intra-domain mapping. Simulation results show that the algorithm can improve the request acceptance rate and reduce the overall average failure rate.
Space-Air-Ground Integrated network(SAGIN) is a heterogeneous network which combines ground network, air network and space network. In SAGIN, a sub-network access algorithm based on reinforcement learning is proposed to make full use of multi-dimensional network resources, improve network delay and reduce packet loss rate. The algorithm learns from the environment iteratively and revises the model constantly, so as to make the optimal access choice. In the simulation experiment, the ASA-RL algorithm has obvious improvement over the comparison algorithm in terms of communication delay and packet loss rate.
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