有界PMC模型下超立方体的额外条件可诊断性

Yongcui Tian, Qiang Zhu, Chaofeng Lv
{"title":"有界PMC模型下超立方体的额外条件可诊断性","authors":"Yongcui Tian, Qiang Zhu, Chaofeng Lv","doi":"10.1109/CACML55074.2022.00072","DOIUrl":null,"url":null,"abstract":"The h-extra conditional diagnosability is different from the traditional diagnosability, which restricts that each component has no fewer than $h+1$ processors after the deletion of the faulty sets in the system. The $(f_{1}, f_{2})$ -BPMC model is a combination of the PMC model and BGM model, assuming that the upper bound number of failed processors is $f_{1}$ and no more than $f_{2}$ failed processors that can evaluate a faulty processor as non-faulty. In this paper, inspired by the $(f_{1}, f_{2})$ - BPMC model, we propose a diagnosis model called $f$ -BPMC model by relaxing the restriction of $f_{1}$. In this model, it only assumes that at most $f$ failed processors for a given system that can evaluate faulty processors as non-faulty. We then study the h-extra conditional diagnosability of interconnection networks under the $f$ -BPMC model and explore some of its properties. Finally, the h-extra conditional diagnosability is applied to hypercubes under the $f$ -BPMC model.","PeriodicalId":137505,"journal":{"name":"2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML)","volume":"17 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Extra Conditional Diagnosability of Hypercubes under the Bounded PMC Model\",\"authors\":\"Yongcui Tian, Qiang Zhu, Chaofeng Lv\",\"doi\":\"10.1109/CACML55074.2022.00072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The h-extra conditional diagnosability is different from the traditional diagnosability, which restricts that each component has no fewer than $h+1$ processors after the deletion of the faulty sets in the system. The $(f_{1}, f_{2})$ -BPMC model is a combination of the PMC model and BGM model, assuming that the upper bound number of failed processors is $f_{1}$ and no more than $f_{2}$ failed processors that can evaluate a faulty processor as non-faulty. In this paper, inspired by the $(f_{1}, f_{2})$ - BPMC model, we propose a diagnosis model called $f$ -BPMC model by relaxing the restriction of $f_{1}$. In this model, it only assumes that at most $f$ failed processors for a given system that can evaluate faulty processors as non-faulty. We then study the h-extra conditional diagnosability of interconnection networks under the $f$ -BPMC model and explore some of its properties. Finally, the h-extra conditional diagnosability is applied to hypercubes under the $f$ -BPMC model.\",\"PeriodicalId\":137505,\"journal\":{\"name\":\"2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML)\",\"volume\":\"17 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CACML55074.2022.00072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CACML55074.2022.00072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

h-extra条件可诊断性与传统的可诊断性不同,传统的可诊断性限制在系统中删除故障集后,每个部件的处理器数量不少于$h+1$。$(f_{1}, f_{2})$ -BPMC模型是PMC模型和BGM模型的结合,假设故障处理器的上界数为$f_{1}$,且不超过$f_{2}$,故障处理器可以评估为非故障。本文在$(f_{1}, f_{2})$ -BPMC模型的启发下,通过放宽$f_{1}$的限制,提出了$f$ -BPMC模型。在这个模型中,它只假设给定系统中最多有$f$个故障处理器,可以将故障处理器评估为非故障处理器。然后,我们研究了$f$ -BPMC模型下互连网络的h-附加条件可诊断性,并探讨了它的一些性质。最后,将h-额外条件可诊断性应用于$f$ -BPMC模型下的超立方体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extra Conditional Diagnosability of Hypercubes under the Bounded PMC Model
The h-extra conditional diagnosability is different from the traditional diagnosability, which restricts that each component has no fewer than $h+1$ processors after the deletion of the faulty sets in the system. The $(f_{1}, f_{2})$ -BPMC model is a combination of the PMC model and BGM model, assuming that the upper bound number of failed processors is $f_{1}$ and no more than $f_{2}$ failed processors that can evaluate a faulty processor as non-faulty. In this paper, inspired by the $(f_{1}, f_{2})$ - BPMC model, we propose a diagnosis model called $f$ -BPMC model by relaxing the restriction of $f_{1}$. In this model, it only assumes that at most $f$ failed processors for a given system that can evaluate faulty processors as non-faulty. We then study the h-extra conditional diagnosability of interconnection networks under the $f$ -BPMC model and explore some of its properties. Finally, the h-extra conditional diagnosability is applied to hypercubes under the $f$ -BPMC model.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信