Journal of Systems Engineering and Electronics ›› 2024, Vol. 35 ›› Issue (4): 842-854.doi: 10.23919/JSEE.2024.000071

• EMERGING DEVELOPMENTS ON SPACE-TEERRESTRIAL INTEGRATED NETWORK AND RELATED KEY TECHNOLOGIES • Previous Articles    

Dynamic access task scheduling of LEO constellation based on space-based distributed computing

Wei LIU1,2,*(), Yifeng JIN1,2(), Lei ZHANG1,2(), Zihe GAO1,2(), Ying TAO1,2()   

  1. 1 Institute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing 100094, China
    2 Innovation Center of Satellite Communication System, China National Space Administration, Beijing 100094, China
  • Received:2023-04-06 Online:2024-08-18 Published:2024-08-06
  • Contact: Wei LIU E-mail:emcf431@163.com;jyfcast@outlook.com;leizhang200@163.com;biblejiayou@163.com;tao.ying@126.com
  • About author:
    LIU Wei was born in 1993. He received his B.S. degree from Harbin Engineering University, Harbin, China, in 2015, and Ph.D. degree from Beihang University, Beijing, China, in 2020. He is currently an engineer of Institute of Telecommunication and Navigation Satellites with China Academy of Space Technology. His research focuses on the design of satellite communication system, distributed computing, cloud computing, edge computing, and artifical intelligence. E-mail: emcf431@163.com

    JIN Yifeng was born in 1995. He received his Ph.D. degree in communication and information systems from Peking University, Beijing, China in 2022, and now works in the Institute of Telecommunication and Navigation Satellite, China Academy of Space Technology as an engineer. His research interests are satellite communication, resource allocation, and space-terrestrial networks. E-mail: jyfcast@outlook.com

    ZHANG Lei was born in 1987. He received his B.E. degree in communication engineering and M.E. degree in electromagnetic theory and microwave engineering from Beijing Institute of Technology, Beijing, China, in 2008 and 2010. He was a visiting fellow with the French Institute of Aeronautics and Astronautics, Toulouse, France, in 2018, and now works in the Institute of Telecommunication and Navigation Satellite, China Academy of Space Technology as an engineer. His research interest includes design of satellite communication system. E-mail: leizhang200@163.com

    GAO Zihe was born in 1983. He received his B.S degree in electronics and information engineering, M.E. degree in signal and information processing, and Ph.D degree in information and communication engineering from Harbin Institute of Technology, Harbin, China, in 2005, 2007, and 2011, respectively. He has been engaged in the development planning, system demonstration, and key technology research of satellite communication E-mail: biblejiayou@163.com

    TAO Ying was born in 1974. She received her B.E. degree in wireless communication from Beijing Jiaotong University, Beijing, China, in 1997, and Ph.D. degree in communication and information system from Beijing Jiaotong University, Beijing, China, in 2004. Her research interest is design of satellite communication system. E-mail: tao.ying@126.com
  • Supported by:
    This work was supported by the National Key Research and Development Program of China (2021YFB2900603) and the National Natural Science Foundation of China (61831008).

Abstract:

A dynamic multi-beam resource allocation algorithm for large low Earth orbit (LEO) constellation based on on-board distributed computing is proposed in this paper. The allocation is a combinatorial optimization process under a series of complex constraints, which is important for enhancing the matching between resources and requirements. A complex algorithm is not available because that the LEO on-board resources is limited. The proposed genetic algorithm (GA) based on two-dimensional individual model and uncorrelated single paternal inheritance method is designed to support distributed computation to enhance the feasibility of on-board application. A distributed system composed of eight embedded devices is built to verify the algorithm. A typical scenario is built in the system to evaluate the resource allocation process, algorithm mathematical model, trigger strategy, and distributed computation architecture. According to the simulation and measurement results, the proposed algorithm can provide an allocation result for more than 1500 tasks in 14 s and the success rate is more than 91% in a typical scene. The response time is decreased by 40% compared with the conditional GA.

Key words: beam resource allocation, distributed computing, low Earth obbit (LEO) constellation, spacecraft access, task scheduling