(1)Beijing Normal University;(2)AMSS,CAS;(3)North China University of Water Conservancy and Electric Power, Zhengzhou
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THE CONDITIONAL DIAGNOSABILITY OF SHUFFLE-CUBES
Min XU(1);Xiaodong HU(2); Songpu SHANG(3)
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(1)Beijing Normal University;(2)AMSS,CAS;(3)North China University of Water Conservancy and Electric Power, Zhengzhou
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文章历史+
收稿日期
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出版日期
2009-04-09
1900-01-01
2010-02-25
发布日期
2010-02-25
摘要
In the application of multiple-processor systems some processors or links in a system may not function properly, thus the fault diagnosis is one of the most important issues in the analysis and maintenance of those systems. For the practical fault diagnosis systems, the probability that all neighboring processors of a processor are faulty simultaneously is very small. Thus, the conditional diagnosability, which is a new metric for evaluating such systems, assumes that every fault set does not contain all neighbors of any processor in the system. In this paper, the authors show that the -dimensional shuffle-cube has the conditional diagnosability of for and .
Abstract
In the application of multiple-processor systems some processors or links in a system may not function properly, thus the fault diagnosis is one of the most important issues in the analysis and maintenance of those systems. For the practical fault diagnosis systems, the probability that all neighboring processors of a processor are faulty simultaneously is very small. Thus, the conditional diagnosability, which is a new metric for evaluating such systems, assumes that every fault set does not contain all neighbors of any processor in the system. In this paper, the authors show that the -dimensional shuffle-cube has the conditional diagnosability of for and .
Min XU
, Xiaodong HU
, Songpu SHANG. , {{custom_author.name_cn}}.
THE CONDITIONAL DIAGNOSABILITY OF SHUFFLE-CUBES. 系统科学与复杂性(英文), 2010, 23(1): 81-090 https://doi.org/10.1007/s11424-010-9271-6
Min XU
, Xiaodong HU
, Songpu SHANG. , {{custom_author.name_en}}.
THE CONDITIONAL DIAGNOSABILITY OF SHUFFLE-CUBES. Journal of Systems Science and Complexity, 2010, 23(1): 81-090 https://doi.org/10.1007/s11424-010-9271-6
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