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The Diagnosability of Wheel Networks with Missing Edges under the Comparison Model

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  • Wei Feng

    (School of Mathematics and Information Science, Henan Normal University, Xinxiang 453007, China
    Institute of Discrete Mathematics, College of Mathematics and Physics, Inner Mongolia University for Nationalities, Tongliao 028043, China)

  • Shiying Wang

    (School of Mathematics and Information Science, Henan Normal University, Xinxiang 453007, China)

Abstract

The diagnosability is an essential subject for the reliability of a multiple CPU system. As a celebrated topology structure of interconnection networks, an n -dimensional wheel network C W n has numerous great features. In this paper, we discuss the diagnosability of C W n with missing edges under the comparison model. Both the local diagnosability and the strong local diagnosability feature are studied; this feature depicts the equivalence of the local diagnosability of a node and its degree. We demonstrate that C W n ( n ≥ 6 ) possesses this feature, containing the strong feature even with up to 2 n − 4 missing edges in it, and the outcome is ideal regarding the amount of missing edges.

Suggested Citation

  • Wei Feng & Shiying Wang, 2020. "The Diagnosability of Wheel Networks with Missing Edges under the Comparison Model," Mathematics, MDPI, vol. 8(10), pages 1-16, October.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:10:p:1818-:d:430317
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    References listed on IDEAS

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    1. Zhang, Guozhen & Wang, Dajin, 2019. "Structure connectivity and substructure connectivity of bubble-sort star graph networks," Applied Mathematics and Computation, Elsevier, vol. 363(C), pages 1-1.
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