Extra diagnosability and good-neighbor diagnosability of n-dimensional alternating group graph AGn under the PMC model
Extra diagnosability and good-neighbor diagnosability of n-dimensional alternating group graph AGn under the PMC model
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PMC模型下n维交替群图AG(n)的额外可诊断性和邻域可诊断性
DOI:
10.1016/j.tcs.2019.05.034
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发表时间:
2019-11
影响因子:
1.1
通讯作者:
Wang Xiaoding
中科院分区:
文献类型:
--
作者:
Huang Yanze;Lin Limei;Xu Li;Wang Xiaoding
The h-extra diagnosability and g-good-neighbor diagnosability are two important diagnostic strategies at system-level that can significantly enhance the system's self-diagnosing capability. The h-extra diagnosability ensures that every component of the system after removing a set of faulty vertices has at least h+ 1 vertices. The g-good-neighbor diagnosability guarantees that after removing some faulty vertices, every vertex in the remaining system has at least g neighbors. In this paper, we analyze the extra diagnosability and good-neighbor diagnosability in a well-known n-dimensional alternating group graph A G n proposed for multiprocessor systems under the PMC model. We first establish that the 1-extra diagnosability of A G n (n≥ 5) is 4 n− 10. Then we prove that the 2-extra diagnosability of A G n (n≥ 5) is 6 n− 17. Next, we address that the 3-extra diagnosability of A G n (n≥ 5) is 8 n− 25. Finally, we obtain that the g-restricted connectivity and the g-good-neighbor diagnosability of A G n (n≥ 5) are (2 g+ 2) n− 2 g+ 2− 4+ g and (2 g+ 2) n− 2 g+ 2− 4+ 2 g for 1≤ g≤ 2, respectively.
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影响因子:
0.7
作者:
Meimei Gu;Rongxia Hao;Dongxue Yang
通讯作者:
Dongxue Yang
影响因子:
4
作者:
Wei Yulong;Xu Min
通讯作者:
Xu Min
DOI:
10.2174/2213275910666161207162427
发表时间:
2017-01
期刊:
Recent Patents on Computer Science
影响因子:
--
作者:
Ji Wang
通讯作者:
Ji Wang
DOI:
10.1016/j.tcs.2008.11.012
发表时间:
2009-03
期刊:
Theor. Comput. Sci.
影响因子:
--
作者:
Ping-Ying Tsai;Jung-Sheng Fu;Gen-Huey Chen
通讯作者:
Ping-Ying Tsai;Jung-Sheng Fu;Gen-Huey Chen
DOI:
10.12988/ams.2015.510679
发表时间:
2015
期刊:
Applied mathematical sciences
影响因子:
--
作者:
Weiping Han;Shiying Wang
通讯作者:
Weiping Han;Shiying Wang