The g-Good-Neighbor Conditional Diagnosability of Exchanged Crossed Cube under the MM* Model

The g-Good-Neighbor Conditional Diagnosability of Locally Twisted Cubes

In the work of Peng et al. in 2012, a new measure was proposed for fault diagnosis of systems: namely, g-good-neighbor conditional diagnosability, which requires that any faultfree vertex has at least g fault-free neighbors in the system. In this paper, we establish the g-good-neighbor conditional diagnosability of locally twisted cubes under the PMC model and the MM∗ model.

The g-good-neighbor conditional diagnosability of hypercube under PMC model

The Tightly Super 2-good-neighbor connectivity and 2-good-neighbor Diagnosability of Crossed Cubes

Mass data processing and complex problem solving have higher and higher demands for performance of multiprocessor systems. Many multiprocessor systems have interconnection networks (networks for short) as underlying topologies and a network is usually represented by a graph where nodes represent processors and links represent communication links between processors. The network determines the pe...

Some Properties of the g-Good-Neighbor (g-Extra) Diagnosability of a Multiprocessor System

Diagnosability of a multiprocessor system is one important study topic. In 2012, Peng et al. proposed a measure for fault tolerance of the system, which is called the g-good-neighbor diagnosability that restrains every fault-free node containing at least g fault-free neighbors. In 2015, Zhang et al. proposed a measure for fault diagnosis of the system, namely, g-extra diagnosability, which rest...

Conditional diagnosability of hypercubes under the comparison diagnosis model

Processor fault diagnosis plays an important role in multiprocessor systems for reliable computing, and the diagnosability of many well-known networks has been explored. Lai et al. proposed a novel measure of diagnosability, called conditional diagnosability, by adding an additional condition that any faulty set cannot contain all the neighbors of any vertex in a system. We make a contribution ...