Volume 51 Issue 9
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RAN H M. Airborne sensor multi-task scheduling algorithm based on slide time window[J]. Journal of Beijing University of Aeronautics and Astronautics,2025,51(9):2968-2978 (in Chinese) doi: 10.13700/j.bh.1001-5965.2023.0488
Citation: RAN H M. Airborne sensor multi-task scheduling algorithm based on slide time window[J]. Journal of Beijing University of Aeronautics and Astronautics,2025,51(9):2968-2978 (in Chinese) doi: 10.13700/j.bh.1001-5965.2023.0488

Airborne sensor multi-task scheduling algorithm based on slide time window

doi: 10.13700/j.bh.1001-5965.2023.0488
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  • Corresponding author: E-mail:ranhuaming7245@163.com
  • Received Date: 27 Jul 2023
  • Accepted Date: 22 Sep 2023
  • Available Online: 18 Sep 2025
  • Publish Date: 13 Oct 2023
  • Aiming at the problem that the multi-task scheduling efficiency of the airborne sensor task management system was reduced due to the execution time window conflicts among multiple task requests, the task scheduling constraint information, include the forward slide time window and the back slide time window of each task, is depicted according to the task request information, such as the executable time window of each task request, and a multi-task scheduling algorithm for the airborne sensor is designed based on the slide time window. Firstly, task requests that can be executed within the scheduling period are selected, and a list of tasks to be scheduled is generated based on priority sorting. Then, multiple time slices are formed by calculating the time overlap relationship between each task to be scheduled and each existing scheduling scheme, and the scheduling scheme set is continuously updated by determining whether the task to be scheduled can be inserted into the extended time slice. Finally, the optimal airborne sensor task scheduling scheme is selected from the scheduling scheme set. The simulation results show that the median scheduling efficiency of the designed algorithm can reach over 96.52% of the optimal algorithm’s scheduling efficiency, and the scheduling efficiency and computational time of the designed algorithm are rarely affected by the scheduling scale and granularity of the task time, the designed algorithm has strong adaptability.

     

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