{"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}
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.