Hierarchical scheduling for real-time agile satellite task scheduling in a dynamic environment. Issue 2 (15th January 2019)

• Record Type: Journal Article
• Authors: He, Lei; Liu, Xiao-Lu; Chen, Ying-Wu; Xing, Li-Ning; Liu, Ke
• Is Part Of: Advances in space research. Volume 63:Issue 2(2019)
• Page Start: 897
• Page End: 912
• Publication Date: 2019-01-15
• Subjects: Agile satellite -- Cloud coverage -- Hierarchical scheduling -- Dynamic environment -- Ant colony algorithm; Space sciences -- Periodicals; Astronautics -- Periodicals; Geophysics -- Periodicals; 500.505
• DOI: 10.1016/j.asr.2018.10.007
• Languages: English
• ISSNs: 0273-1177

Abstract

Highlights: We study the problem of agile satellite scheduling with real-time cloud coverage. A hierarchical scheduling model is established. A hierarchical scheduling algorithm based on the ant colony algorithm is proposed. The influence of environmental changes is well-mitigated by the proposed method. The proposed method can greatly reduce the CPU time and increase the total profit. Abstract: The imaging processes of optical satellites can be easily affected by unexpected environmental changes, such as changes in cloud coverage. Given the difficulty to predict environmental uncertainties, traditional offline scheduling methods need a follow-up re-scheduling process that responds to real-time environmental information. This repetitive scheduling processes make the offline fine scheduling process a waste of computational resources. Additionally, the offline scheduling method is quite complex owing to its lack of a hierarchy mechanism. To solve these problems, we propose a hierarchical scheduling method for the real-time scheduling problem. This method divides the scheduling process into three steps: pre-assignment, rough scheduling, and fine scheduling. A hierarchical scheduling algorithm based on ant colony algorithm is proposed. Tests with 36 scenarios show that the calculation time is efficiently reduced with this new mechanism. With this consideration of the dynamic environment, the re-scheduling process becomes unnecessary, meaning the wasting of computational resources is avoided and the solution profit is improved.