4.7 Article

Flexible Task Scheduling in Data Relay Satellite Networks

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAES.2021.3115587

关键词

Task analysis; Satellites; Relays; Scheduling; Space vehicles; Antennas; Scheduling algorithms; Conflict resolution; constrained optimization; data relay satellite networks; iterative search; task scheduling

资金

  1. National Natural Science Foundation of China [62073341]
  2. Natural Science Fund for Distinguished Young Scholars of Hunan Province [2019JJ20026]
  3. Natural Science Foundation of Hunan Province [2020JJ4119]

向作者/读者索取更多资源

This paper proposes a novel application mode and algorithm for task scheduling in data relay satellite networks. Experimental results demonstrate the competitive performance of the proposed algorithm in terms of task completion ratio.
The task-schedulingalgorithm is a key module to satisfy various complex user requirements, and improve the usage flexibility and efficiency of data relay satellites networks (DRSN). In this context, we first propose a novel application mode for DRSN, in which users are allowed to submit multiple optional service time windows and specify a preferred antenna as well as an expected execution duration for each task. Meanwhile, the start time of a service time window can be adjusted within a specified range. A mathematical programming model that maximizes the completion ratio of tasks and the expectation satisfaction of users is established. Moreover, a conflict resolution-assisted iterative task-scheduling algorithm (CRITS) is designed, composing of five closely dependent operators: resource matching, service durations generation, conflict evaluation, conflict resolution, and solution update. To verify the effectiveness of the proposed CRITS, extensive experiments are carried out. The experimental results demonstrate the competitive performance of CRITS in addressing the DRSN scheduling problem. In comparison with two heuristic algorithms (heuristic algorithm based on time-freedom degree and a heuristic algorithm based on task priority) and a meta-heuristic algorithm (adaptive variable neighborhood descent combined with a tabu list), the proposed CRITS increases the overall completion ratio of tasks by 6.65, 10.26, and 10.96%, respectively.

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