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.
Unmanned Aerial Vehicle (UAV) into Mobile Edge Computing (MEC) systems can effectively expand their flexibility and coverage. The current research trend in UAV-assisted MEC is mainly focused on optimizing flight control and minimizing energy consumption. However, there is a lack of research on task scheduling in UAV-assisted MEC scenarios. This paper proposes a two-stage task scheduling method that minimizes the task processing cost while optimizing task execution order to reduce the execution time of tasks. The results of the study show that the proposed algorithm outperforms other baseline methods in terms of completing all tasks with the shortest execution time. This further validates the efficiency of the proposed algorithm and its potential for improving the system efficiency of UAV-assisted MEC.
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.
Resource scheduling technology as an important means to achieve the optimal allocation of SAGIN resources, plays a vital role in Earth observation, emergency communications and other fields, through the in-depth understanding and analysis of the research status of the integrated network resource scheduling field, the current resource scheduling technology is not yet perfect, it is difficult to meet the multi-satellite collaboration, network topology real-time changes, massive users as the characteristics of the scheduling needs. Starting from the research point of multi-dimensional resources, this paper considers the synergy between resources, proposes a multi-dimensional resource vector model, and on this basis proposes a multi-dimensional resource collaborative optimization scheduling algorithm to achieve unified scheduling from the global perspective. In the simulation experiment, it is proved that the indicators such as the number of task completions, total tasks revenues, average revenue and scheduling decision-making time can be effectively improved, among which the number of task completions is increased by 10%-30%, the total tasks revenue is increased by 30%-60%, and the scheduling decision-making time is saved by about 30%.
The space-ground integrated network (SGIN) is a future communication network that integrates different dimensions networks to form a new network application scenario based on the terrestrial network and extended by satellite network. SGIN can cover natural spaces such as space, ground, ocean, etc., and can provide users with more diverse network services. As a new type of network, SGIN also faces the problem of network ossification in traditional network. In traditional network, network virtualization can overcome this problem effectively. However, most of the current researches are based on terrestrial network models or satellite network models, which cannot adapt to the dynamic and heterogeneous nature of SGIN. In order to meet the demand of SGIN for network virtualization, we establish a SGIN time evolution graph model and propose a virtual network embedding algorithm (CD-VNE). The algorithm selects the network sub community with the most abundant physical resources through community detection technology, which can reduce the consumption of link bandwidth resources and the risk of satellite link failure. The simulation results show that CD-VNE can increase the Revenue/Cost ratio and acceptance ratio.
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.
Space-Air-Ground Integrated network (SAGIN) that integrates satellite system, air network and ground communication network has attracted extensive research interests in recent years, for its high value to practical services and its wide applications in communication. Nevertheless, it also faces many unprecedented challenges due to its heterogeneity, selforganization, time variability and other characteristics. In order to solve the problems of unstable inter-domain neighbor relationship, frequent routing update and slow routing convergence in space-air-ground integrated network, a link fault recovery method of space-air-ground integrated network based on time sequence link weight graph is proposed in this paper. This method is based on the infrastructure of software-defined network, and introduces time-varying characteristics, designs a dynamic model of link weight change, and proposes a link fault recovery method. The simulation results show that by considering link resources and node resources, compared with the link detection and recovery scheme of softwaredefined satellite network, this method can effectively solve the problem that it is unable to build an effective recovery path because of the unstable inter domain relationship in the space-air-ground integrated network, and can effectively find a recovery path with the lower path cost, low end-to-end delay and high reliability.
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