基于时间和任务重要度的系统弹性恢复研究

Research on System Resilience Recovery Based on Time and Task Importance

作为系统重要属性之一的弹性受到越来越多的关注,而系统在受损后的规定时间内应当尽量多的恢复关键任务,所以相应的恢复策略的制定以及能够恢复到什么程度对系统的弹性来说是十分重要的。针对这种情况,文章提出一种新的考虑时间以及任务重要度等因素的适应度函数,利用遗传算法求解规定时间内系统恢复任务重要度的最大值,获得模型的满意解。仿真算例中,通过对比表明应用此算法的系统拥有更高的弹性恢复能力,证明了该模型和算法的有效性。

As one of the important attributes of the system,more and more attention has been paid to the resilience of the sys⁃tem,and the system should recover as many key tasks as possible within the specified time after the damage.Therefore,the formula⁃tion of the corresponding recovery strategy and the extent to which it can be recovered are very important for the resilience of the sys⁃tem.In view of this situation,this paper proposes a new fitness function that takes into account factors such as time and task impor⁃tance.The genetic algorithm is used to solve the maximum value of the system recovery task importance within a specified time to ob⁃tain a satisfactory solution for the model.In the simulation example,the comparison shows that the system using this algorithm has higher resilience recovery ability,which proves the effectiveness of the model and algorithm.