• Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
成果搜索

author:

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

Indexed by:

EI

Abstract:

The k k-ary nn-cube QnkQnk is one of the most popular interconnection networks engaged as the underlying topology of data center networks, on-chip networks, and parallel and distributed systems. Due to the increasing probability of faulty edges in large-scale networks and extensive applications of the Hamiltonian path, it becomes more and more critical to investigate the fault tolerability of interconnection networks when embedding the Hamiltonian path. However, since the existing edge fault models in the current literature only focus on the entire status of faulty edges while ignoring the important information in the edge dimensions, their fault tolerability is narrowed to a minimal scope. This article first proposes the concept of the partitioned fault model to achieve an exponential scale of fault tolerance. Based on this model, we put forward two novel indicators for the bipartite networks (including QknQnk with even k k), named partition-edge fault-tolerant Hamiltonian laceability and partition-edge fault-tolerant hyper-Hamiltonian laceability. Then, we exploit these metrics to explore the existence of Hamiltonian paths and unpaired 2-disjoint path cover in kk-ary nn-cubes with large-scale faulty edges. Moreover, we prove that all these results are optimal in the sense that the number of edge faults tolerated has attended to the best upper bound. Our approach is the first time that can still embed a Hamiltonian path and an unpaired 2-disjoint path cover into the kk-ary nn-cube even if the faulty edges grow exponentially. © 1968-2012 IEEE.

Keyword:

Embeddings Fault tolerance Fault tolerant computer systems Geometry Hamiltonians Interconnection networks (circuit switching) Network topology

Community:

  • [ 1 ] [Zhuang, Hongbin]Fuzhou University, College of Computer and Data Science, Fuzhou; 350108, China
  • [ 2 ] [Li, Xiao-Yan]Fuzhou University, College of Computer and Data Science, Fuzhou; 350108, China
  • [ 3 ] [Chang, Jou-Ming]National Taipei University of Business, Institute of Information and Decision Sciences, Taipei; 10051, Taiwan
  • [ 4 ] [Lin, Cheng-Kuan]National Yang-Ming Chiao Tung University, Department of Computer Science, Hsinchu; 30010, Taiwan
  • [ 5 ] [Liu, Ximeng]Fuzhou University, College of Computer and Data Science, Fuzhou; 350108, China

Reprint 's Address:

Email:

Show more details

Related Keywords:

Related Article:

Source :

IEEE Transactions on Computers

ISSN: 0018-9340

Year: 2023

Issue: 11

Volume: 72

Page: 3245-3258

3 . 6

JCR@2023

3 . 6 0 0

JCR@2023

JCR Journal Grade:2

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

Affiliated Colleges:

Online/Total:93/9941353
Address:FZU Library(No.2 Xuyuan Road, Fuzhou, Fujian, PRC Post Code:350116) Contact Us:0591-22865326
Copyright:FZU Library Technical Support:Beijing Aegean Software Co., Ltd. 闽ICP备05005463号-1