Connectivity and diagnosability of the complete Josephus cube networks under h-extra fault-tolerant model

被引:0
|
作者
Huang, Zhaoman [1 ]
Zhang, Mingzu [1 ]
Lee, Chia-Wei [2 ]
机构
[1] Xinjiang Univ, Dept Coll Math & Syst Sci, Urumqi 830046, Peoples R China
[2] Univ Taipei, Dept Comp Sci, 1 Ai Guo West Rd, Taipei, Taiwan
基金
中国国家自然科学基金;
关键词
Interconnection networks; Diagnosability and reliability; h-Extra connectivity; h-Extra diagnosability; Complete Josephus cube; CONDITIONAL DIAGNOSABILITY; HYPERCUBE; COMPONENT;
D O I
10.1016/j.tcs.2024.114925
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The h-extra connectivity and the h-extra diagnosability are key parameters for evaluating the reliability and fault-tolerance of the interconnection networks of the multiprocessor systems, and play an important role in designing and maintaining interconnection networks. Recently, various self-diagnostic models have emerged to assess the fault-tolerance in interconnection networks. These interconnection networks are typically expressed by a connected graph G(V, E ). For a non- complete graph G and h >= 0, the h-extra cut signifies a vertex subset R of G , whose removal results in G - R disconnected, with each remaining component containing at least h + 1 vertices. And the h-extra connectivity of G is defined as the minimum cardinality of all h-extra cuts of G . The h-extra diagnosability for a graph G denotes the maximum number of detectable faulty vertices when focusing on these h-extra faulty sets only. The complete Josephus cube CJCn, a variant of Q n , exhibits superior properties compared to hypercube Q n , and also boasts higher connectivity. In this study, with the help of the exact value of the h-extra connectivity of CJCn, the explicit expression of h-extra diagnosability of CJCn under both the PMC model for n >= 5 and 1 <= h <= [ n -3 2 j and the MM* model for n >= 5 and 2 <= h <= [ n -3 2 j are identified to share the same value (h + 1)n - ( h -1 ) + 1. 2
引用
收藏
页数:9
相关论文
共 33 条
  • [1] The H-extra Conditional Diagnosability of Burnt Pancake Networks under the PMC Model
    Wang, Rong
    Zhu, Qiang
    PROCEEDINGS FIRST INTERNATIONAL CONFERENCE ON ELECTRONICS INSTRUMENTATION & INFORMATION SYSTEMS (EIIS 2017), 2017, : 561 - 566
  • [2] The h-extra connectivity and h-extra conditional diagnosability of Bubble-sort star graphs
    Zhu, Q.
    Zhang, J.
    Li, L. L.
    DISCRETE APPLIED MATHEMATICS, 2018, 251 : 322 - 333
  • [3] Fault-tolerant routing for complete Josephus cubes
    Loh, PKK
    Hsu, WJ
    PARALLEL COMPUTING, 2004, 30 (9-10) : 1151 - 1167
  • [4] The h-extra connectivity of the star graph Networks
    Zhu, Qiang
    Chen, Jing
    Li, Lili
    PROCEEDINGS FIRST INTERNATIONAL CONFERENCE ON ELECTRONICS INSTRUMENTATION & INFORMATION SYSTEMS (EIIS 2017), 2017, : 555 - 560
  • [5] h-extra r-component connectivity of interconnection networks with application to hypercubes
    Li, Bi
    Lan, Jingfen
    Ning, Wantao
    Tian, Yongcui
    Zhang, Xin
    Zhu, Qiang
    THEORETICAL COMPUTER SCIENCE, 2021, 895 : 68 - 74
  • [6] Assessing reliability in Complete Josephus Cube networks via strongly Menger edge-connectivity
    Huang, Zhaoman
    Yang, Yayu
    Zhang, Mingzu
    Yang, Xing
    JOURNAL OF SUPERCOMPUTING, 2025, 81 (01)
  • [7] A Complete Fault Tolerant Method for Extra Fault Diagnosability of Alternating Group Graphs
    Lin, Limei
    Huang, Yanze
    Xu, Li
    Hsieh, Sun-Yuan
    IEEE TRANSACTIONS ON RELIABILITY, 2021, 70 (03) : 957 - 969
  • [8] Link fault tolerance of BC networks and folded hypercubes on h-extra r-component edge-connectivity
    Yang, Yayu
    Zhang, Mingzu
    Meng, Jixiang
    APPLIED MATHEMATICS AND COMPUTATION, 2024, 462
  • [9] Fault-Tolerant Hamiltonian Connectivity and Fault-Tolerant Hamiltonicity of the Fully Connected Cubic Networks
    Ho, Tung-Yang
    Lin, Cheng-Kuan
    JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2009, 25 (06) : 1855 - 1862
  • [10] The Relationship Between the g-Extra Connectivity and the g-Extra Diagnosability of Networks Under the MM* Model
    Yuan, Jun
    Liu, Aixia
    Wang, Xi
    COMPUTER JOURNAL, 2021, 64 (06) : 921 - 928