Load-Balancing Method for LEO Satellite Edge-Computing Networks Based on the Maximum Flow of Virtual Links
With the increasing number of satellites in orbit, traditional scheduling methods can no longer satisfy the increasing data demands of users. The timeliness of remote sensing images with large data volumes is poor in the backhaul process through low-earth-orbit (LEO) satellite networks. To address t...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9893795/ |
| _version_ | 1811265297418551296 |
|---|---|
| author | Yuqi Wang Jibin Che Ningyuan Wang Liang Liu Nan Wu Xiaoqing Zhong Xiaodong Han |
| author_facet | Yuqi Wang Jibin Che Ningyuan Wang Liang Liu Nan Wu Xiaoqing Zhong Xiaodong Han |
| author_sort | Yuqi Wang |
| collection | DOAJ |
| description | With the increasing number of satellites in orbit, traditional scheduling methods can no longer satisfy the increasing data demands of users. The timeliness of remote sensing images with large data volumes is poor in the backhaul process through low-earth-orbit (LEO) satellite networks. To address the above problems, we propose an edge-computing load-balancing method for LEO satellite networks based on the maximum flow of virtual links. First, the minimum rectangle composed of computing nodes is determined by the source and destination nodes of the transmission task under the configuration of the 2D-Torus topology of LEO satellite networks. Second, edge computing virtual links are established between computing nodes and users. Third, the Ford-Fulkerson algorithm is used to obtain the maximum flow of the topology with virtual links. Finally, a strategy is generated for computing and transmission resource allocation. The simulation results show that the proposed method can optimize the total capacity of the multi-node information backhaul in the remote sensing scenario of LEO satellite networks. The effectiveness of the proposed algorithm is verified in several special scenarios. |
| first_indexed | 2024-04-12T20:21:13Z |
| format | Article |
| id | doaj.art-272ad7cd3246495bb1edbe64189ff52e |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T20:21:13Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-272ad7cd3246495bb1edbe64189ff52e2022-12-22T03:17:59ZengIEEEIEEE Access2169-35362022-01-011010058410059310.1109/ACCESS.2022.32072939893795Load-Balancing Method for LEO Satellite Edge-Computing Networks Based on the Maximum Flow of Virtual LinksYuqi Wang0https://orcid.org/0000-0002-8767-5312Jibin Che1Ningyuan Wang2https://orcid.org/0000-0002-6062-9519Liang Liu3https://orcid.org/0000-0002-3117-3874Nan Wu4Xiaoqing Zhong5Xiaodong Han6https://orcid.org/0000-0002-2535-4214Institute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing, ChinaKey Laboratory of Electronic Information Countermeasure and Simulation Technology, Ministry of Education, Xidian University, Xi’an, ChinaInstitute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing, ChinaInstitute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing, ChinaBeijing Institute of Control Engineering, Beijing, ChinaInstitute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing, ChinaInstitute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing, ChinaWith the increasing number of satellites in orbit, traditional scheduling methods can no longer satisfy the increasing data demands of users. The timeliness of remote sensing images with large data volumes is poor in the backhaul process through low-earth-orbit (LEO) satellite networks. To address the above problems, we propose an edge-computing load-balancing method for LEO satellite networks based on the maximum flow of virtual links. First, the minimum rectangle composed of computing nodes is determined by the source and destination nodes of the transmission task under the configuration of the 2D-Torus topology of LEO satellite networks. Second, edge computing virtual links are established between computing nodes and users. Third, the Ford-Fulkerson algorithm is used to obtain the maximum flow of the topology with virtual links. Finally, a strategy is generated for computing and transmission resource allocation. The simulation results show that the proposed method can optimize the total capacity of the multi-node information backhaul in the remote sensing scenario of LEO satellite networks. The effectiveness of the proposed algorithm is verified in several special scenarios.https://ieeexplore.ieee.org/document/9893795/2D-torus topologyinformation backhaulLEO satellite networksload balancingvirtual links |
| spellingShingle | Yuqi Wang Jibin Che Ningyuan Wang Liang Liu Nan Wu Xiaoqing Zhong Xiaodong Han Load-Balancing Method for LEO Satellite Edge-Computing Networks Based on the Maximum Flow of Virtual Links IEEE Access 2D-torus topology information backhaul LEO satellite networks load balancing virtual links |
| title | Load-Balancing Method for LEO Satellite Edge-Computing Networks Based on the Maximum Flow of Virtual Links |
| title_full | Load-Balancing Method for LEO Satellite Edge-Computing Networks Based on the Maximum Flow of Virtual Links |
| title_fullStr | Load-Balancing Method for LEO Satellite Edge-Computing Networks Based on the Maximum Flow of Virtual Links |
| title_full_unstemmed | Load-Balancing Method for LEO Satellite Edge-Computing Networks Based on the Maximum Flow of Virtual Links |
| title_short | Load-Balancing Method for LEO Satellite Edge-Computing Networks Based on the Maximum Flow of Virtual Links |
| title_sort | load balancing method for leo satellite edge computing networks based on the maximum flow of virtual links |
| topic | 2D-torus topology information backhaul LEO satellite networks load balancing virtual links |
| url | https://ieeexplore.ieee.org/document/9893795/ |
| work_keys_str_mv | AT yuqiwang loadbalancingmethodforleosatelliteedgecomputingnetworksbasedonthemaximumflowofvirtuallinks AT jibinche loadbalancingmethodforleosatelliteedgecomputingnetworksbasedonthemaximumflowofvirtuallinks AT ningyuanwang loadbalancingmethodforleosatelliteedgecomputingnetworksbasedonthemaximumflowofvirtuallinks AT liangliu loadbalancingmethodforleosatelliteedgecomputingnetworksbasedonthemaximumflowofvirtuallinks AT nanwu loadbalancingmethodforleosatelliteedgecomputingnetworksbasedonthemaximumflowofvirtuallinks AT xiaoqingzhong loadbalancingmethodforleosatelliteedgecomputingnetworksbasedonthemaximumflowofvirtuallinks AT xiaodonghan loadbalancingmethodforleosatelliteedgecomputingnetworksbasedonthemaximumflowofvirtuallinks |