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以数据中继卫星光网络系统资源、任务和约束条件为参量,以任务对资源的选择为优化对象,提出了一种基于自适应遗传算法的数据中继卫星光网络资源调度算法。综合考虑多中继星、多时间窗口、多光学天线以及任务优先级要求,建立调度模型;采用“当前任务调度时间的确定”和“后续任务可见时间窗口的更新”的调度操作,对不同资源的任务集合进行调度安排并实现了可见时间窗口的动态更新,获得调度任务的总权值并将其作为参量计算适应度值,最后通过改进的自适应遗传算法对不同调度方案进行寻优。以3颗中继星、12颗用户星,6个光天线,60个任务为条件设置了仿真场景,仿真结果表明该算法在收敛速度、调度效率方面具有优势,适应于多任务、多天线的数据中继卫星光网络系统资源调度。
Taking the resources, tasks and constraints of data relay satellite optical network system as parameters and the task selection of resources as the optimization object, an adaptive optical network resource scheduling algorithm for data relay satellite optical network is proposed. Considering multi-relay star, multi-time window, multi-optical antenna and task priority requirements, a scheduling model is established; the scheduling operation of “update of time window can be seen by the determination of current task scheduling time” and “subsequent task” , Scheduled scheduling of different resources task set and realized the dynamic update of visible time window, obtained the total weight of the scheduled task and used it as a parameter to calculate the fitness value. Finally, through the improved adaptive genetic algorithm to different scheduling schemes Optimistic. The simulation scenario is set on the condition of three relay stars, 12 user stars, 6 optical antennas and 60 tasks. The simulation results show that this algorithm has advantages in terms of convergence rate and scheduling efficiency and is suitable for multi-tasking, multi-antenna Data relay satellite optical network system resource scheduling