Service Throughput And Hierarchical Characteristics Oriented LEO Clustering In Double-Layer Space-Based Satellite Networks

In order to provide a network with low cost,fast speed and global coverage,the plan of using a large number of low earth orbit(LEO)satellites and a small number of geosynchronous orbit(GEO)satellites to jointly form a multilayered satellite network is gradually accepted.However,this plan will make the overall structure of the satellite network complex,so the academic community proposes to simplify the satellite network by clustering LEO satellites.As for clustering,the existing research is mainly focused on optimizing the structure of the network itself,or adopting a simplified method that is convenient for routing algorithm processing.With the continuous development of satellite networks and the increasing number of services,existing clustering methods cannot improve the service carrying performance of satellite networks.This paper studies how to obtain the LEO satellite clustering strategy according to the service.The main research services in this paper are divided into two categories,namely,the best possible service without the reservation system,and the quality assurance service using the reservation system.An efficient algorithm for calculating the LEO satellite clustering scheme directly from service characteristics is proposed.Aiming at the best-effort reachable service without reservation system,this paper introduces service prediction,maps the starting point,end point and bandwidth of the predicted service to the satellite’s physical link and accumulates them into weights,and sets the threshold to select the link into clusters,and designs and optimizes the clustering algorithm for service throughput.Subsequently,this paper carries out a wide range of simulation experiments on the proposed algorithm,and selects a contrast algorithm to analyze and compare the effect of this algorithm.Experiments show that compared with the contrast algorithm,this algorithm has a better effect on the service bandwidth throughput indicator,with a stable optimization of about 2%-3%.Aiming at reservation services with quality requirements,this paper aims at the main indicators of quality of service(QoS):priority,latency,and stability.By introducing cross weights to optimize stability,selecting the gateway node to optimize latency,designing impact factors to orient optimization latency and stability,etc.,to comprehensively design and optimize clustering algorithms,and improve the quality of service of various services.Experiments show that compared with the contrast algorithm,the clustering algorithm proposed in this paper has about 1%optimization on the total QoS indicator,among which the delay is about 1.5%-2%optimization and the stability is 1%-1.5%optimization.To sum up,the service-based LEO satellite clustering algorithm proposed in this paper can improve the performance of the service in the clustered LEO satellite network,which has certain practical significance.