A Survey for Conditional Diagnosability of Alternating Group Networks

研究成果: Conference contribution

摘要

Fault diagnosis of processors has played an essential role when evaluating the reliability of multiprocessor systems. In many novel multiprocessor systems, their diagnosability has been extensively explored. Conditional diagnosability is a useful measure for evaluating diagnosability by adding a further condition that all neighbors of every node in the system do not fail at the same time. In this paper, we study the conditional diagnosability of n-dimensional alternating group networks under the PMC model, and obtain the results, and. In addition, for the isomorphism property between with, namely star graphs, the above results can be extended to, and we have and for. It is worth noting that the conditional diagnosability is about six times the degree of and, which is very different from general networks with a multiple of four.

原文English
主出版物標題Computing and Combinatorics - 26th International Conference, COCOON 2020, Proceedings
編輯Donghyun Kim, R.N. Uma, Zhipeng Cai, Dong Hoon Lee
發行者Springer Science and Business Media Deutschland GmbH
頁面640-651
頁數12
ISBN(列印)9783030581497
DOIs
出版狀態Published - 2020
事件26th International Conference on Computing and Combinatorics, COCOON 2020 - Atlanta, United States
持續時間: 2020 八月 292020 八月 31

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12273 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference26th International Conference on Computing and Combinatorics, COCOON 2020
國家/地區United States
城市Atlanta
期間20-08-2920-08-31

All Science Journal Classification (ASJC) codes

  • 理論電腦科學
  • 電腦科學(全部)

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