Resource Scheduling Algorithm Based on DQN in Satellite CDN

With the rapid development of space and information fi eld, hot content distribution intensive scenes will become one of the key directions of satellite network application, and satellite content delivery network (CDN) network is an important means to improve the effi ciency of air and space content...

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Main Authors: Jiaran ZHANG, Yating YANG, Tian SONG
Format: Article
Language:zho
Published: Post&Telecom Press Co.,LTD 2022-12-01
Series:天地一体化信息网络
Subjects:
Online Access:http://www.j-sigin.com.cn/zh/article/doi/10.11959/j.issn.2096-8930.2022042/
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author Jiaran ZHANG
Yating YANG
Tian SONG
author_facet Jiaran ZHANG
Yating YANG
Tian SONG
author_sort Jiaran ZHANG
collection DOAJ
description With the rapid development of space and information fi eld, hot content distribution intensive scenes will become one of the key directions of satellite network application, and satellite content delivery network (CDN) network is an important means to improve the effi ciency of air and space content distribution.In the architecture of satellite CDN network, due to the uneven time and space of business requirements, the scarcity of satellite resources and the insuffi cient adaptability of existing scheduling algorithms, scheduling algorithms for satellite resources are faced with problems such as high resource dimension, many computing states and large amount of computation, which will reduce the accuracy, response speed and computing performance of scheduling decisions.To solve this problem, a resource scheduling algorithm based on Deep Q-Learning (DQN) algorithm was proposed to improved the effi ciency and accuracy of satellite resource scheduling, and intelligently and quickly perceived the resource situation to make scheduling decisions.Firstly, the user requests were classifi ed, and the shortest path set that the satellite could communicated with was calculated according to the time-varying trajectory of the satellite and the resources of the satellite and the ground.After that, the related information of satellites and users was quantifi ed by Markov model modeling, and the optimal CDN storage node of satellites was calculated by DQN algorithm, which achieved the eff ects of reduced user request delay, reduced satellite-ground resource occupancy rate and improved cache hit rate.
format Article
id doaj-art-da3ef1932cb84b2fb92378f38003ed8c
institution Kabale University
issn 2096-8930
language zho
publishDate 2022-12-01
publisher Post&Telecom Press Co.,LTD
record_format Article
series 天地一体化信息网络
spelling doaj-art-da3ef1932cb84b2fb92378f38003ed8c2025-01-15T02:48:13ZzhoPost&Telecom Press Co.,LTD天地一体化信息网络2096-89302022-12-013455459531420Resource Scheduling Algorithm Based on DQN in Satellite CDNJiaran ZHANGYating YANGTian SONGWith the rapid development of space and information fi eld, hot content distribution intensive scenes will become one of the key directions of satellite network application, and satellite content delivery network (CDN) network is an important means to improve the effi ciency of air and space content distribution.In the architecture of satellite CDN network, due to the uneven time and space of business requirements, the scarcity of satellite resources and the insuffi cient adaptability of existing scheduling algorithms, scheduling algorithms for satellite resources are faced with problems such as high resource dimension, many computing states and large amount of computation, which will reduce the accuracy, response speed and computing performance of scheduling decisions.To solve this problem, a resource scheduling algorithm based on Deep Q-Learning (DQN) algorithm was proposed to improved the effi ciency and accuracy of satellite resource scheduling, and intelligently and quickly perceived the resource situation to make scheduling decisions.Firstly, the user requests were classifi ed, and the shortest path set that the satellite could communicated with was calculated according to the time-varying trajectory of the satellite and the resources of the satellite and the ground.After that, the related information of satellites and users was quantifi ed by Markov model modeling, and the optimal CDN storage node of satellites was calculated by DQN algorithm, which achieved the eff ects of reduced user request delay, reduced satellite-ground resource occupancy rate and improved cache hit rate.http://www.j-sigin.com.cn/zh/article/doi/10.11959/j.issn.2096-8930.2022042/satellite CDNDQNresource arrangement
spellingShingle Jiaran ZHANG
Yating YANG
Tian SONG
Resource Scheduling Algorithm Based on DQN in Satellite CDN
天地一体化信息网络
satellite CDN
DQN
resource arrangement
title Resource Scheduling Algorithm Based on DQN in Satellite CDN
title_full Resource Scheduling Algorithm Based on DQN in Satellite CDN
title_fullStr Resource Scheduling Algorithm Based on DQN in Satellite CDN
title_full_unstemmed Resource Scheduling Algorithm Based on DQN in Satellite CDN
title_short Resource Scheduling Algorithm Based on DQN in Satellite CDN
title_sort resource scheduling algorithm based on dqn in satellite cdn
topic satellite CDN
DQN
resource arrangement
url http://www.j-sigin.com.cn/zh/article/doi/10.11959/j.issn.2096-8930.2022042/
work_keys_str_mv AT jiaranzhang resourceschedulingalgorithmbasedondqninsatellitecdn
AT yatingyang resourceschedulingalgorithmbasedondqninsatellitecdn
AT tiansong resourceschedulingalgorithmbasedondqninsatellitecdn