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Volume 43 Issue 4
Apr.  2021
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Yifan CHENG, Zhicheng QU, Gengxin ZHANG. Traffic Modeling for Low Earth Orbit Satellite Constellation Internet of Things[J]. Journal of Electronics & Information Technology, 2021, 43(4): 1050-1056. doi: 10.11999/JEIT200091
Citation: Yifan CHENG, Zhicheng QU, Gengxin ZHANG. Traffic Modeling for Low Earth Orbit Satellite Constellation Internet of Things[J]. Journal of Electronics & Information Technology, 2021, 43(4): 1050-1056. doi: 10.11999/JEIT200091

Traffic Modeling for Low Earth Orbit Satellite Constellation Internet of Things

doi: 10.11999/JEIT200091
Funds:  The National Natural Science Foundation of China(91738201)
  • Received Date: 2020-02-11
  • Rev Recd Date: 2020-09-14
  • Available Online: 2020-09-23
  • Publish Date: 2021-04-20
  • With the continuous development of the Internet of Things(IoT), its business demands show a trend of diversification and globalization. As the ground Internet of Things can not cover the whole world, the satellite IoT, especially the Low Earth Orbit Satellite Constellation (LEOSC) IoT, can supplement and extend the ground network. Due to the wide coverage and high dynamic characteristics of the LEOSC IoT system, there are significant differences between it and the ground IoT in terms of traffic statistics. In order to make reasonable and efficient use of limited resources on board, the traffic model of global Internet of Things based on LEOSC is studied in this paper. Combined with diversified traffic characteristics and satellite communication system characteristics, the framework of global IoT traffic model is obtained by using statistical modeling theory. What’s more, an access strategy based on the highest priority is proposed to enable the device node to select the satellite in real time. The simulation results show that the Poisson process can be used to simulate approximately the superposition process of asynchronous traffic commonly exist in LEOSC IoT, and due to the high dynamic nature of low earth orbit satellite, its traffic source changes at high speed, resulting in high Peak-to-Average Ratio(PAR) of traffic.
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