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Fault tolerance of recursive match networks based on g-good-neighbor fault pattern

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  • Zhou, Qianru
  • Liu, Hai
  • Cheng, Baolei
  • Wang, Yan
  • Han, Yuejuan
  • Fan, Jianxi

Abstract

The rapid informatization and digitalization of the society heavily rely on the extensive use of parallel and distributed, networked computer systems. It is important for large-scale parallel and distributed systems to be able to detect and tolerate faulty vertices in the network. A network's fault status can often be characterized with the network's connectivity and diagnosability. The connectivity/diagnosability can be defined under various conditions. This paper is concerned with the connectivity/diagnosability under the “g-good-neighbor condition”, which can more accurately measure a network's fault status. In this paper, we propose a new class of recursive networks, named recursive match networks (RMNs), which contain the well-known BCube and BC networks. We determine the RMNs' g-good-neighbor connectivity and g-good-neighbor conditional diagnosability under the classic MM* and PMC diagnostic models for g≥0. Since the RMN is a more general network covering the BCube and BC networks, our results can be directly applied to these two networks.

Suggested Citation

  • Zhou, Qianru & Liu, Hai & Cheng, Baolei & Wang, Yan & Han, Yuejuan & Fan, Jianxi, 2024. "Fault tolerance of recursive match networks based on g-good-neighbor fault pattern," Applied Mathematics and Computation, Elsevier, vol. 461(C).
    • Handle: RePEc:eee:apmaco:v:461:y:2024:i:c:s0096300323004873
    DOI: 10.1016/j.amc.2023.128318
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    References listed on IDEAS

    as
    1. Zhu, Wen-Han & Hao, Rong-Xia & Feng, Yan-Quan & Lee, Jaeun, 2023. "The 3-path-connectivity of the k-ary n-cube," Applied Mathematics and Computation, Elsevier, vol. 436(C).
    2. Liu, Xuemei & Meng, Jixiang & Sabir, Eminjan, 2023. "Component connectivity of the data center network DCell," Applied Mathematics and Computation, Elsevier, vol. 444(C).
    3. Guo, Jia & Lu, Mei, 2018. "Conditional diagnosability of the SPn graphs under the comparison diagnosis model," Applied Mathematics and Computation, Elsevier, vol. 336(C), pages 249-256.
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