A novel multi-satellite and multi-task scheduling method based on task network graph aggregation

The task scheduling timeliness problem on satellite networks is crucial to realizing the Space-Terrestrial Integrated Network (STIN). Traditional methods interpret the satellite mission scheduling problem as a linear or non-linear programming problem, having ignored the complex relationships between missions. To improve the timeliness of task scheduling in a multi-satellite and multi-task scenario, we investigate a network graph structure that explains the task correlation. Then, we propose a multi-layer network graph aggregation model for tasks with similarity and relevance features. Further, we transform the task scheduling problem into a zero–one programming problem and design task scheduling algorithms to solve the task scheduling timeliness problem. Finally, we simulate and emulate real-world data as the experimental dataset for comparison with the three baseline algorithms. The experimental results show that the method in this paper has distinct advantages and advancements.