Abstract
Diagnosability of a multiprocessor system is one important study topic. In 2015, Zhang et al. proposed a new measure for fault diagnosis of the system, namely, g-extra diagnosability, which restrains that every fault-free component has at least (g + 1) fault-free nodes. As a favorable topology structure of interconnection networks, the n-dimensional alternating group graph AGn has many good properties. In this paper, we give that the 2-extra diagnosability of AGn is 6n - 17 for n≥ 5 under the PMC model and MM* model.
Highlights
Many multiprocessor systems take interconnection networks as underlying topologies and a network is usually represented by a graph where nodes represent processors and links represent communication links between processors
We give that the 2-extra diagnosability of AGn is 6n − 17 for n ≥ 5 under the PMC model and MM* model
We investigate the problem of 2-extra diagnosability of the n-dimensional alternating group graph AGn under the PMC model and MM* model
Summary
Many multiprocessor systems take 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. In 2005, Lai et al [3] introduced a restricted diagnosability of multiprocessor systems called conditional diagnosability They consider the situation that any fault set cannot contain all the neighbors of any vertex in a system. In [6], they studied the g-good-neighbor diagnosability of the n-dimensional hypercube under the PMC model. In [7], Wang and Han studied the g-good-neighbor diagnosability of the n-dimensional hypercube under the MM* model. In [10] [11], Wang et al studied the g-good-neighbor diagnosability of CΓn under the PMC model and MM* model for g = 1,2. In [12], they studied the g-extra diagnosability of the n-dimensional hypercube under the PMC model and MM* model. We give that the 2-extra diagnosability of AGn is 6n − 17 for n ≥ 5 under the PMC model and MM* model
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