运筹学学报 ›› 2019, Vol. 23 ›› Issue (1): 97-103.doi: 10.15960/j.cnki.issn.1007-6093.2019.01.011

• 运筹学 • 上一篇    下一篇

单圈图生成的凯莱图UGn在PMC模型和MM*模型下的1好邻诊断度

任佳敏1, 冯伟1, 赵凌琪2, 王世英3, 吉日木图1,*   

  1. 1. 内蒙古民族大学数学学院, 内蒙古通辽 028043;
    2. 内蒙古民族大学计算机科学与技术学院, 内蒙古通辽 028043;
    3. 河南师范大学数学与信息科学学院, 河南新乡 453007
  • 收稿日期:2017-09-11 出版日期:2019-03-15 发布日期:2019-03-15
  • 通讯作者: 吉日木图 E-mail:jrmt@sina.com
  • 基金资助:

    国家自然科学基金(Nos.61262018,61370001,61402317),内蒙古民族大学科学研究项目(No.NMDGP17106)

The 1-good-neighbor diagnosability of the Cayley graphs UGn generated by unicyclic graphs under the PMC model and the MM* model

REN Jiamin1, FENG Wei1, ZHAO Lingqi2, WANG Shiying3, JIRIMUTU1,*   

  1. 1. College of Mathematics, Inner Mongolia University for Nationalities, Tongliao 028043, Inner Mongolia Autonomous Region, China;
    2. College of Computer Science and Technology, Inner Mongolia University for Nationalities, Tongliao 028043, Inner Mongolia Autonomous Region, China;
    3. School of Mathematics and Information Science, Henan Normal University, Xinxiang 453007, Henan, China
  • Received:2017-09-11 Online:2019-03-15 Published:2019-03-15

摘要:

多处理系统的诊断度是一个重要的研究课题.一种新的系统故障诊断方法称为g好邻诊断度,它是限制每个无故障点至少包含g个无故障的邻点.单圈图生成的凯莱图UGn作为一种极好的互联网络拓扑结构有许多好的性质.现证明了当n ≥ 4时,单圈图生成的凯莱图UGn在PMC模型下的1好邻诊断度是2n-1;当n ≥ 5时,UGn在MM*模型下的1好邻诊断度是2n-1.

关键词: 互联网络, 诊断度, 凯莱图, PMC模型, MM*模型

Abstract:

Diagnosability of a multiprocessor system is an important study topic. A new measure for fault diagnosis of the system is called g-good-neighbor diagnosability that restrains every fault-free node containing at least g fault-free neighbors. As a famous topology structure of interconnection networks, the Cayley graph UGn generated by unicyclic graphs has many good properties. In this paper, we prove that the 1-good-neighbor diagnosability of the Cayley graph UGn generated by unicyclic graphs is 2n-1 under the PMC model for n ≥ 4; the 1-good-neighbor diagnosability of the Cayley graph UGn generated by unicyclic graphs is 2n-1 under the MM* model for n ≥ 5.

Key words: interconnection network, diagnosability, Cayley graph, PMC model, MM* model

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