Puning Zhang;Ziyun Xian;Mingjun Liao;Haiyun Huang;Junyan Yang
{"title":"Adaptive Routing Mechanism for LEO Satellite Network Based on Control Domain Partition","authors":"Puning Zhang;Ziyun Xian;Mingjun Liao;Haiyun Huang;Junyan Yang","doi":"10.1109/TGCN.2024.3425458","DOIUrl":null,"url":null,"abstract":"Low Earth Orbit (LEO) satellite network has the characteristics of low delay, low propagation loss, high bandwidth, and seamless coverage, which is the cornerstone of space-air-ground integrated network. However, the complex topology and time-varying link state of LEO lead to extremely unstable data routing. Existing routing research faces the challenges of large link information update delay, high routing table storage, and query overhead, which seriously affect satellite data transmission, onboard computing, and storage efficiency. To address the above issues, an adaptive routing mechanism based on control domain partition is proposed, considering the dynamic time-varying characteristics of LEO satellite constellation topology and inter-satellite link. Specifically, a non-dominated sorting-based control domain partition architecture is designed to manage the satellite domain for reducing control delay and improving link information update efficiency. Then a distributed routing method for control domain division is proposed to sense the link status of adjacent control domains rather than the entire satellite network, so as to alleviate the problems of high storage and query complexity and slow update of link information. Furthermore, a link situation aware routing decision-making method is devised to accurately perceive the link situation and achieve optimal path decision-making. The simulation results demonstrate that the proposed mechanism respectively improves the network performance by about 12%, 22%, and 14% in terms of end-to-end average delay, packet loss rate, and throughput.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"9 1","pages":"70-82"},"PeriodicalIF":5.3000,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Green Communications and Networking","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10589577/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Low Earth Orbit (LEO) satellite network has the characteristics of low delay, low propagation loss, high bandwidth, and seamless coverage, which is the cornerstone of space-air-ground integrated network. However, the complex topology and time-varying link state of LEO lead to extremely unstable data routing. Existing routing research faces the challenges of large link information update delay, high routing table storage, and query overhead, which seriously affect satellite data transmission, onboard computing, and storage efficiency. To address the above issues, an adaptive routing mechanism based on control domain partition is proposed, considering the dynamic time-varying characteristics of LEO satellite constellation topology and inter-satellite link. Specifically, a non-dominated sorting-based control domain partition architecture is designed to manage the satellite domain for reducing control delay and improving link information update efficiency. Then a distributed routing method for control domain division is proposed to sense the link status of adjacent control domains rather than the entire satellite network, so as to alleviate the problems of high storage and query complexity and slow update of link information. Furthermore, a link situation aware routing decision-making method is devised to accurately perceive the link situation and achieve optimal path decision-making. The simulation results demonstrate that the proposed mechanism respectively improves the network performance by about 12%, 22%, and 14% in terms of end-to-end average delay, packet loss rate, and throughput.