PMC模型下ACS-HCN的条件诊断算法

Condition diagnosis algorithm of ACS-HCN under PMC model

受到自然界中蚂蚁觅食行为的启发,通过对蚁群系统(ant colony system,ACS)中蚂蚁的觅食路径进行分析,得到一系列重要的结论,将其与超立方体网络(hypercube network,HCN)中结点的故障诊断相结合,提出一种条件诊断算法,即快速定位诊断(fast location diagnosis,FLD)算法,时间复杂度为 O(n),n 表示觅食点的个数。与变体立方体网络的条件可诊断、星型网络的条件可诊断相比,ACS-HCN的条件诊断算法具有时间复杂度小、诊断效率高的优点。

Inspired by ants foraging behavior,through analysing ants foraging path of ant colony system (ant colony system,ACS),a series of important conclusions were obtained and combined with the nodes fault diagnosis of hypercube network (HCN),a condition diagnosis algorithm called fast location diagnosis (FLD) was proposed.The time complexity here was O (n),where n represented the number of forage nodes.Compared with the condition of variable cube network and star network,the condition diagnosis algorithm of ACS-HCN has lower time complexity and higher diagnosis efficiency.