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author:

Li, X.-Y. (Li, X.-Y..) [1] | Lin, Z. (Lin, Z..) [2] | Zhuang, H. (Zhuang, H..) [3] | Chang, J.-M. (Chang, J.-M..) [4]

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Scopus

Abstract:

Connectivity indicators are commonly used to evaluate system fault tolerance and reliability. However, with the high demand for multi-processor systems in high-performance computing and data center networks, the number of processors is getting larger, and the network is getting more complex. Thus, traditional connectivity and other indicators are hardly competent in assessing the reliability of complex networks. The matroidal connectivity and conditional matroidal connectivity are novel connectivity metrics that measure the actual fault-tolerant capability based on the constraints of each network dimension. In this paper, we study matroidal connectivity and conditional matroidal connectivity of the (n,k)-arrangement graph network An,k from the natural perspective of the partition of edge dimension and obtain their theoretically accurate values. Moreover, we conduct numerical analysis to compare matroidal connectivity with other conditional edge connectivities in An,k. Additionally, we explore the distribution pattern of edge failure through simulation experiments in An,k and attain the relation of conditional matroidal connectivity related to network scales. Our investigations include two famous network classes: alternating group graphs and star graphs. © 2024 Elsevier B.V.

Keyword:

Arrangement graph network Conditional matroidal connectivity Fault tolerance Matroidal connectivity Network reliability

Community:

  • [ 1 ] [Li X.-Y.]College of Computer and Data Science, Fuzhou University, Fuzhou, 350108, China
  • [ 2 ] [Lin Z.]College of Computer and Data Science, Fuzhou University, Fuzhou, 350108, China
  • [ 3 ] [Zhuang H.]College of Computer and Data Science, Fuzhou University, Fuzhou, 350108, China
  • [ 4 ] [Chang J.-M.]Institute of Information and Decision Sciences, National Taipei University of Business, Taipei, 10051, Taiwan

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Source :

Theoretical Computer Science

ISSN: 0304-3975

Year: 2025

Volume: 1024

0 . 9 0 0

JCR@2023

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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