Hybrid fault diagnosis capability analysis of regular graphs under the PMC model. Issue 2 (2nd April 2020) - Zhang, Hong; Zhang, Laijiang; Meng, Jixiang
Abstract : Diagnosabilty is an important metric to the capability of fault identification for multiprocessor systems. However, most researches on diagnosability focus on vertex fault. In real circumstances, not only vertex faults take place but also malfunctions may arise. In this paper, we study the diagnosability of k-regular 2-cn graph with missing edges. Let F e be a set of missing edges in graph G with | F e | ≤ k − 5 . We prove that the diagnosability of G − F e is at most δ ( G − F e ) for k ≥ 5 . Furthermore, we obtain that the worst-case diagnosability (h-edge tolerable diagnosability), denoted by t h e ( G ), is maximum number of faulty nodes that a system G can guarantee to locate when the number of faulty links does not exceed h . As applications, the diagnosabilities of many networks with missing edges are determined under the PMC model.