Research on Routing Optimization in Satellite Internet Based on Deep Reinforcement Learning

With the rapid development of satellite communication, the satellite internet is one of the core technologies of 6G network to realize global coverage, full-time access and full scene service.The high dynamics and limited capacity of satellite network lead to a series of management and control chall...

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Main Authors: Linhui WEI, Guowen LIU, Yu LIU, Yumei WANG
Format: Article
Language:zho
Published: Post&Telecom Press Co.,LTD 2022-09-01
Series:天地一体化信息网络
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Online Access:http://www.j-sigin.com.cn/zh/article/doi/10.11959/j.issn.2096-8930.2022033/
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author Linhui WEI
Guowen LIU
Yu LIU
Yumei WANG
author_facet Linhui WEI
Guowen LIU
Yu LIU
Yumei WANG
author_sort Linhui WEI
collection DOAJ
description With the rapid development of satellite communication, the satellite internet is one of the core technologies of 6G network to realize global coverage, full-time access and full scene service.The high dynamics and limited capacity of satellite network lead to a series of management and control challenges such as heterogeneous network management, dynamic resource allocation and so on.Since the machine learning-based technologies have strength in network design, the intelligent architecture of software-defi ned satellite internet was put forward.In view of the intelligent routing in satellite internet, and leverages the deep reinforcement algorithm based on double delayed deep deterministic policy gradient (TD3) to solve the network routing optimization problem.The experimental results showed that compared with DDPG algorithm, the TD3 algorithm reduced the delay by 19.19%.
format Article
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institution Kabale University
issn 2096-8930
language zho
publishDate 2022-09-01
publisher Post&Telecom Press Co.,LTD
record_format Article
series 天地一体化信息网络
spelling doaj-art-2a35eb4b98c44f58a775108e8558c97d2025-01-15T02:48:09ZzhoPost&Telecom Press Co.,LTD天地一体化信息网络2096-89302022-09-013657159531039Research on Routing Optimization in Satellite Internet Based on Deep Reinforcement LearningLinhui WEIGuowen LIUYu LIUYumei WANGWith the rapid development of satellite communication, the satellite internet is one of the core technologies of 6G network to realize global coverage, full-time access and full scene service.The high dynamics and limited capacity of satellite network lead to a series of management and control challenges such as heterogeneous network management, dynamic resource allocation and so on.Since the machine learning-based technologies have strength in network design, the intelligent architecture of software-defi ned satellite internet was put forward.In view of the intelligent routing in satellite internet, and leverages the deep reinforcement algorithm based on double delayed deep deterministic policy gradient (TD3) to solve the network routing optimization problem.The experimental results showed that compared with DDPG algorithm, the TD3 algorithm reduced the delay by 19.19%.http://www.j-sigin.com.cn/zh/article/doi/10.11959/j.issn.2096-8930.2022033/satellite internetsoftware-defi ned networkingdeep reinforcement learningrouting optimization
spellingShingle Linhui WEI
Guowen LIU
Yu LIU
Yumei WANG
Research on Routing Optimization in Satellite Internet Based on Deep Reinforcement Learning
天地一体化信息网络
satellite internet
software-defi ned networking
deep reinforcement learning
routing optimization
title Research on Routing Optimization in Satellite Internet Based on Deep Reinforcement Learning
title_full Research on Routing Optimization in Satellite Internet Based on Deep Reinforcement Learning
title_fullStr Research on Routing Optimization in Satellite Internet Based on Deep Reinforcement Learning
title_full_unstemmed Research on Routing Optimization in Satellite Internet Based on Deep Reinforcement Learning
title_short Research on Routing Optimization in Satellite Internet Based on Deep Reinforcement Learning
title_sort research on routing optimization in satellite internet based on deep reinforcement learning
topic satellite internet
software-defi ned networking
deep reinforcement learning
routing optimization
url http://www.j-sigin.com.cn/zh/article/doi/10.11959/j.issn.2096-8930.2022033/
work_keys_str_mv AT linhuiwei researchonroutingoptimizationinsatelliteinternetbasedondeepreinforcementlearning
AT guowenliu researchonroutingoptimizationinsatelliteinternetbasedondeepreinforcementlearning
AT yuliu researchonroutingoptimizationinsatelliteinternetbasedondeepreinforcementlearning
AT yumeiwang researchonroutingoptimizationinsatelliteinternetbasedondeepreinforcementlearning