Satellite IoT Edge Intelligent Computing: A Research on Architecture

• Published in: Electronics (Basel) Vol. 8; no. 11; p. 1247
• Main Authors: Wei, Junyong, Han, Jiarong, Cao, Suzhi
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2019
• Subjects: Algorithms; Artificial intelligence; Collaboration; Computer architecture; Computer centers; Data processing; Deep learning; Edge computing; Ground stations; High performance computing; Internet of Things; Intersatellite communications; Low earth orbit satellites; Machine learning; Neural networks; Power; Remote sensing; Satellite communications; Satellites; Spectrum allocation; Task analysis; Unmanned aerial vehicles; Wireless networks
• ISSN: 2079-9292; 2079-9292
• DOI: 10.3390/electronics8111247

As the number of satellites continues to increase, satellites become an important part of the IoT and 5G/6G communications. How to deal with the data of the satellite Internet of Things is a problem worth considering and paying attention to. Due to the current on-board processing capability and the limitation of the inter-satellite communication rate, the data acquisition from the satellite has a higher delay and the data utilization rate is lower. In order to use the data generated by the satellite IoT more effectively, we propose a satellite IoT edge intelligent computing architecture. In the article, we analyze the current methods of satellite data processing, combined with the development trend of future satellites, and use the characteristics of edge computing and machine learning to describe the satellite IoT edge intelligent computing architecture. Finally, we verify that the architecture can speed up the processing of satellite data. By demonstrating the performance of different neural network models in the satellite edge intelligent computing architecture, we can find that the lightweight of neural networks can promote the development of satellite IoT edge intelligent computing architecture.