The 1-Good-Neighbor Diagnosability of Alternating Group Graph Networks Under the PMC Model and MM* Model
Jirimutu, Shiying Wang · Recent Advances in Computer Science and Communications · 2017
Background: Many multiprocessor systems have interconnection networks as underlying topologies, also described in various patents, and an interconnection network is usually represented by a graph where nodes represent processors and links represent communication links between processors. For the system, study of the topological properties of its interconnection network is important. In 2012, Peng et al. proposed a new measure for fault diagnosis of the system, namely, the g-goodneighbor diagnosability (which is also called the g-good-neighbor conditional diagnosability), which requires that every fault-free node contains at least g fault-free neighbors. The n-dimensional alternating group graph network ANn has been proved to be an important viable candidate for interconnecting a multiprocessor system. The feature of ANn includes low degree of node, small diameter, symmetry, and high degree of fault-tolerance. Keywords: Interconnection network, graph, diagnosability, alternating group graph network, PMC model, MM* model.