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Analysis of conditional diagnosability for balanced hypercubes

机译:平衡超立方体的条件可诊断性分析

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Fault diagnosis plays an important role in ensuring the reliability of a massive multiprocessor system. The identified faulty processors (nodes) of a diagnosed system will be replaced by fault-free nodes. A measure, called diagnosability, of a system is the maximum number of faulty nodes guaranteed to be identified during the diagnosis process. A new measure for fault diagnosis of a system, namely conditional diagnosability, was proposed to improve the number of identified faulty nodes. In this paper, we study the conditional diagnosability of balanced hypercubes under the PMC model and show that the conditional diagnosability of the n-dimensional balanced hypercube is 4n−3 for n ≥ 1.
机译:故障诊断在确保大型多处理器系统的可靠性中起着重要作用。被诊断系统的已识别故障处理器(节点)将被无故障节点替换。系统的可诊断性度量是在诊断过程中保证能够确定的最大故障节点数。提出了一种用于系统故障诊断的新措施,即条件可诊断性,以提高已识别故障节点的数量。在本文中,我们研究了在PMC模型下平衡超立方体的条件可诊断性,并表明当n≥1时,n维平衡超立方体的条件可诊断性为4n-3。

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