Conditional diagnosability of Cayley graphs generated by wheel graphs under the PMC model

Fault diagnosis of systems is an important area of study in the design and maintenance of multiprocessor systems. In 2005, Lai et al. [12] introduced conditional diagnosability under the assumption that all the neighbors of any processor in a multiprocessor system cannot be faulty at the same time. In this paper, we completely determine the conditional diagnosability of Cayley graphs generated by wheel graphs WG(n) under the PMC model. (C) 2020 Published by Elsevier B.V.

Automated summary

The study completely determines the conditional diagnosability of Cayley graphs generated by wheel graphs under the PMC model, providing important theoretical support for fault diagnosis in multiprocessor systems.