A Novel Load Balancing Scheme for Satellite IoT Networks Based on Spatial–Temporal Distribution of Users and Advanced Genetic Algorithms
Satellite IoT networks (S-IoT-N), which have been a hot issue regarding the next generation of communication, are quite important for the coming era of digital twins and the metaverse because of their performance in sensing and monitoring anywhere, anytime, and anyway, in more dimensions. However, t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/20/7930 |
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| author | Wenliang Lin Zewen Dong Ke Wang Dongdong Wang Yaohua Deng Yicheng Liao Yang Liu Da Wan Bingyu Xu Genan Wu |
| author_facet | Wenliang Lin Zewen Dong Ke Wang Dongdong Wang Yaohua Deng Yicheng Liao Yang Liu Da Wan Bingyu Xu Genan Wu |
| author_sort | Wenliang Lin |
| collection | DOAJ |
| description | Satellite IoT networks (S-IoT-N), which have been a hot issue regarding the next generation of communication, are quite important for the coming era of digital twins and the metaverse because of their performance in sensing and monitoring anywhere, anytime, and anyway, in more dimensions. However, this will cause communication links to face greater traffic loads. Satellite internet networks (SIN) are considered the most possible evolution road, possessing characteristics of many satellites, such as low earth orbit (LEO), the Ku/Ka frequency, and a high data rate. Existing research on load balancing schemes for satellite networks cannot solve the problems of low efficiency under conditions of extremely non-uniform distribution of users (DoU) and dynamic density variances. Therefore, this paper proposes a novel load balancing scheme of adjacent beams for S-IoT-N based on the modeling of spatial–temporal DoU and advanced GA. In our scheme, the PDF of the DoU in the direction of movement of the SSP’s trajectory was modeled first, which provided a multi-directional constraint for the non-uniform distribution of users in S-IoT-N. Fully considering the prior periodicity of satellite movement and the similarity of DoU in different areas, we proposed an adaptive inheritance iteration to optimize the crossover factor and mutation factor for GA for the first time. Based on the proposed improved GA, we obtained the optimal scheme of load balancing under the conditions of the adaptation from the local balancing scheme to global balancing, and a selection of Ser-Beams to access. Finally, the simulations show that the proposed method can improve the average throughput by 3% under specific conditions and improve processing efficiency by 30% on average. |
| first_indexed | 2024-03-09T19:31:10Z |
| format | Article |
| id | doaj.art-dd56b668d1c9428f80b4bd8d70f84e95 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T19:31:10Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-dd56b668d1c9428f80b4bd8d70f84e952023-11-24T02:28:54ZengMDPI AGSensors1424-82202022-10-012220793010.3390/s22207930A Novel Load Balancing Scheme for Satellite IoT Networks Based on Spatial–Temporal Distribution of Users and Advanced Genetic AlgorithmsWenliang Lin0Zewen Dong1Ke Wang2Dongdong Wang3Yaohua Deng4Yicheng Liao5Yang Liu6Da Wan7Bingyu Xu8Genan Wu9The School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaThe School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaSchool of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaScience and Technology on Communication Networks Laboratory, Shijiazhuang 050081, ChinaThe School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaThe School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaThe School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaThe School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaChina Academy of Information and Communications Technology, Beijing 100191, ChinaChina Academy of Space Technology, Beijing 100094, ChinaSatellite IoT networks (S-IoT-N), which have been a hot issue regarding the next generation of communication, are quite important for the coming era of digital twins and the metaverse because of their performance in sensing and monitoring anywhere, anytime, and anyway, in more dimensions. However, this will cause communication links to face greater traffic loads. Satellite internet networks (SIN) are considered the most possible evolution road, possessing characteristics of many satellites, such as low earth orbit (LEO), the Ku/Ka frequency, and a high data rate. Existing research on load balancing schemes for satellite networks cannot solve the problems of low efficiency under conditions of extremely non-uniform distribution of users (DoU) and dynamic density variances. Therefore, this paper proposes a novel load balancing scheme of adjacent beams for S-IoT-N based on the modeling of spatial–temporal DoU and advanced GA. In our scheme, the PDF of the DoU in the direction of movement of the SSP’s trajectory was modeled first, which provided a multi-directional constraint for the non-uniform distribution of users in S-IoT-N. Fully considering the prior periodicity of satellite movement and the similarity of DoU in different areas, we proposed an adaptive inheritance iteration to optimize the crossover factor and mutation factor for GA for the first time. Based on the proposed improved GA, we obtained the optimal scheme of load balancing under the conditions of the adaptation from the local balancing scheme to global balancing, and a selection of Ser-Beams to access. Finally, the simulations show that the proposed method can improve the average throughput by 3% under specific conditions and improve processing efficiency by 30% on average.https://www.mdpi.com/1424-8220/22/20/7930load balancingsatellite networkInternet of Thingsgenetic algorithmbeam hopping |
| spellingShingle | Wenliang Lin Zewen Dong Ke Wang Dongdong Wang Yaohua Deng Yicheng Liao Yang Liu Da Wan Bingyu Xu Genan Wu A Novel Load Balancing Scheme for Satellite IoT Networks Based on Spatial–Temporal Distribution of Users and Advanced Genetic Algorithms Sensors load balancing satellite network Internet of Things genetic algorithm beam hopping |
| title | A Novel Load Balancing Scheme for Satellite IoT Networks Based on Spatial–Temporal Distribution of Users and Advanced Genetic Algorithms |
| title_full | A Novel Load Balancing Scheme for Satellite IoT Networks Based on Spatial–Temporal Distribution of Users and Advanced Genetic Algorithms |
| title_fullStr | A Novel Load Balancing Scheme for Satellite IoT Networks Based on Spatial–Temporal Distribution of Users and Advanced Genetic Algorithms |
| title_full_unstemmed | A Novel Load Balancing Scheme for Satellite IoT Networks Based on Spatial–Temporal Distribution of Users and Advanced Genetic Algorithms |
| title_short | A Novel Load Balancing Scheme for Satellite IoT Networks Based on Spatial–Temporal Distribution of Users and Advanced Genetic Algorithms |
| title_sort | novel load balancing scheme for satellite iot networks based on spatial temporal distribution of users and advanced genetic algorithms |
| topic | load balancing satellite network Internet of Things genetic algorithm beam hopping |
| url | https://www.mdpi.com/1424-8220/22/20/7930 |
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