Systems Engineering and Electronics ›› 2023, Vol. 45 ›› Issue (5): 1391-1398.doi: 10.12305/j.issn.1001-506X.2023.05.15

• Systems Engineering • Previous Articles    

Task scheduling microservice strategy for space manipulation simulation

Runnan QIN1,*, Wenming XIE1, Jianjiang HUI2, Xiaodong PENG1, Yun LI1   

  1. 1. National Space Science Center, Chinese Academy of Sciences, Beijing 100191, China
    2. Unit 63921 of the PLA, Beijing 100094, China
  • Received:2022-06-21 Online:2023-04-21 Published:2023-04-28
  • Contact: Runnan QIN

Abstract:

Aiming at the exponentially increasing data interaction computing pressure of TB and PB telemetry parameters, load data transmission and other data in large-scale space manipulation simulation experiments, as well as the challenges to the traditional service architecture brought by the concurrent invocation of massive multi-source heterogeneous simulation models, a task scheduling microservice for simulation (S-TSM) solution for space manipulation simulation is constructed. With the help of hybrid microservice scheduling technology, a dual engine dynamic task scheduling platform with the load migration model as the core is established to avoid load balancing shocks and optimize the resource allocation of server nodes. It has the advantages of short load balancing cycle, rapid computing task response, high throughput stability, etc. The experimental results of the field spacecraft test simulation system show that, under the condition of meeting the requirements of massive control simulation task scheduling and high throughput processing of interactive data of control objects, compared with the Xxl-job, Elastic-job, Spring Cloud task scheduling architecture, the average response time of a single service of S-TSM is shortened by 0.10 s, 0.25 s, 0.92 s respectively, and the average load balancing time is shortened by 1.90 s compared with polling, ratio, elastic sharding and other load balancing algorithms, with certain competitiveness.

Key words: space manipulation simulation, microservice, task scheduling, load balancing

CLC Number: 

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