Abstract
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.
Highlights
The Internet of Things (IoT) is one of the new directions for the future development of the Internet, and intelligent networking devices will be connected [1,2]
The satellite IoT can be designed based on satellite constellation, the network topology has Electronics 2019, 8, x FOR PEER REVIEW
The satellite IoT edge computing and the distributed satellite IoT intelligent computing architecture are described in detail
Summary
The Internet of Things (IoT) is one of the new directions for the future development of the Internet, and intelligent networking devices will be connected [1,2]. Compared with the method of transmitting satellite image data to the satellite ground station cloud computing data center and using deep learning for centralized processing, this paper proposes a method using edge intelligent computing processing and describes the satellite IoT edge intelligent computing architecture. We use the more powerful on-board computing power in the future to place the deep-learning algorithm model at the source of satellite data generation to achieve edge intelligent computing. This architecture can reduce the amount of data transmitted from satellites, reduce data processing and communication delays, improve the bandwidth utilization of inter-satellite links, and reduce the pressure on data processing of satellite ground stations.
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