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An Edge Computing Algorithm Based on Multi-Level Star Sensor Cloud

Siyu Ren1, Shi Qiu2,*, Keyang Cheng3

1 The Open University of Chengdu, Major in Computer Application, Chengdu, 610000, China
2 Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences. Xi’an, 710119, China
3 School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, 212013, China

* Corresponding Author: Shi Qiu. Email: email

(This article belongs to this Special Issue: Advances in Edge Intelligence for Internet of Things)

Computer Modeling in Engineering & Sciences 2023, 136(2), 1643-1659. https://doi.org/10.32604/cmes.2023.025248

Abstract

Star sensors are an important means of autonomous navigation and access to space information for satellites. They have been widely deployed in the aerospace field. To satisfy the requirements for high resolution, timeliness, and confidentiality of star images, we propose an edge computing algorithm based on the star sensor cloud. Multiple sensors cooperate with each other to form a sensor cloud, which in turn extends the performance of a single sensor. The research on the data obtained by the star sensor has very important research and application values. First, a star point extraction model is proposed based on the fuzzy set model by analyzing the star image composition, which can reduce the amount of data computation. Then, a mapping model between content and space is constructed to achieve low-rank image representation and efficient computation. Finally, the data collected by the wireless sensor is delivered to the edge server, and a different method is used to achieve privacy protection. Only a small amount of core data is stored in edge servers and local servers, and other data is transmitted to the cloud. Experiments show that the proposed algorithm can effectively reduce the cost of communication and storage, and has strong privacy.

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Cite This Article

Ren, S., Qiu, S., Cheng, K. (2023). An Edge Computing Algorithm Based on Multi-Level Star Sensor Cloud. CMES-Computer Modeling in Engineering & Sciences, 136(2), 1643–1659.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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