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author:

Zhuang, Hongbin (Zhuang, Hongbin.) [1] | Guo, Wenzhong (Guo, Wenzhong.) [2] | Li, Xiao-Yan (Li, Xiao-Yan.) [3] | Liu, Ximeng (Liu, Ximeng.) [4] | Lin, Cheng-Kuan (Lin, Cheng-Kuan.) [5]

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EI

Abstract:

With the rapid expansion of the scale of multiprocessor systems, the importance of fault tolerance and fault diagnosis is increasingly concerned. For an interconnection network G, the h-component connectivity is an important indicator for evaluating the fault tolerance of G, which is defined as the minimum number of vertices whose deletion will disconnect G such that the remaining has at least h components. The h-component diagnosability, a newly precise diagnosis strategy to analyze the reliability of G, is the diagnosability under the condition that the number of components is at least h in the resulting graph after removing the faulty processor set. The t/k-diagnosability is a classic imprecise diagnosis strategy, which can identify up to t faulty processors by sacrificing accuracy to a certain extent, namely misdiagnosing at most k fault-free processors. In this paper, we investigate some combinatorial properties and the fault tolerance ability of the n-dimensional Bicube network, denoted by BQn. Then we first prove that the (h+1)-component connectivity of BQn is [Formula presented] (n≥6, 1≤h≤n−1). Moreover, we derive that the (h+1)-component diagnosability of BQn is [Formula presented] under the PMC model and MM model (n≥7, 1≤h≤n−3). Furthermore, under the PMC model, we propose the t/k-diagnosis algorithm of BQn and then derive that BQn is [Formula presented]-diagnosable (n≥6, 0≤k≤n−2). © 2021 Elsevier B.V.

Keyword:

Fault detection Fault tolerance Interconnection networks (circuit switching)

Community:

  • [ 1 ] [Zhuang, Hongbin]College of Computer and Data Science, Fuzhou University, Fuzhou; 350108, China
  • [ 2 ] [Zhuang, Hongbin]Fujian Provincial Key Laboratory of Information Security of Network Systems, Fuzhou University, Fuzhou; 350108, China
  • [ 3 ] [Guo, Wenzhong]College of Computer and Data Science, Fuzhou University, Fuzhou; 350108, China
  • [ 4 ] [Li, Xiao-Yan]College of Computer and Data Science, Fuzhou University, Fuzhou; 350108, China
  • [ 5 ] [Li, Xiao-Yan]Fujian Provincial Key Laboratory of Information Security of Network Systems, Fuzhou University, Fuzhou; 350108, China
  • [ 6 ] [Liu, Ximeng]College of Computer and Data Science, Fuzhou University, Fuzhou; 350108, China
  • [ 7 ] [Liu, Ximeng]Fujian Provincial Key Laboratory of Information Security of Network Systems, Fuzhou University, Fuzhou; 350108, China
  • [ 8 ] [Lin, Cheng-Kuan]College of Computer and Data Science, Fuzhou University, Fuzhou; 350108, China

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Source :

Theoretical Computer Science

ISSN: 0304-3975

Year: 2021

Volume: 896

Page: 145-157

1 . 0 0 2

JCR@2021

0 . 9 0 0

JCR@2023

ESI HC Threshold:106

JCR Journal Grade:4

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 9

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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