The 1-good-neighbor diagnosability of unidirectional hypercubes under the PMC model

Shangwei Lin and Wenli Zhang

Applied Mathematics and Computation, 2020, vol. 375, issue C

Abstract: The hypercubes are a famous class of networks for multiprocessor systems and the unidirectional hypercubes are hypercube interconnection topologies with simplex unidirectional links. Under the classic PMC model, each processor in a multiprocessor system tests a subset of its neighbors. The collection of tests in this system can be modeled by a directed graph. The diagnosability of a system is the maximum number of faulty processors that the system may identify according to the outcomes of the tests, and the g-good-neighbor diagnosability is a more accurate indicator than the diagnosability. In this paper, we first determine the 1-good-neighbor connectivity of unidirectional hypercubes and then determine the diagnosability and 1-good-neighbor diagnosability of hypercube networks when unidirectional hypercubes are used as the collection of tests under the PMC model.

Keywords: Network; PMC Diagnosis model; Hypercube; Faulty diagnosability; Conditional connectivity (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:375:y:2020:i:c:s0096300320300606

DOI: 10.1016/j.amc.2020.125091

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