The diagnosability of a system is defined as the maximum number of faulty processors that the system can guarantee to identify, which plays an important role in measuring of the reliability of multiprocessor systems. In the work of Peng et al. in 2012, they proposed a new measure for fault diagnosis of systems, namely, g-good-neighbor conditional diagnosability. It is defined as the diagnosability of a multiprocessor system under the assumption that every fault-free node contains at least g fault-free neighbors, which can measure the reliability of interconnection networks in heterogeneous environments more accurately than traditional diagnosability. The k-ary n-cube is a family of popular networks. In this study, we first investigate and determine the R g -connectivity of k-ary n-cube for 0 g n: Based on this, we determine the g-good-neighbor conditional diagnosability of k-ary n-cube under the PMC model and MM Ã model for k ! 4; n ! 3 and 0 g n: Our study shows the g-good-neighbor conditional diagnosability of k-ary n-cube is several times larger than the classical diagnosability of k-ary n-cube.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.