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Pancake graphs: Structural properties and conditional diagnosability
Journal of Combinatorial Optimization ( IF 0.9 ) Pub Date : 2022-07-25 , DOI: 10.1007/s10878-022-00877-8
Nai-Wen Chang , Hsuan-Jung Wu , Sun-Yuan Hsieh

Because of the increasing size of multi-processor systems, processor-fault diagnosis has played critical role in measuring reliability. The diagnosability of numerous well-known multiprocessor systems has been widely investigated. The conditional diagnosability is a new measure of diagnosability by restricting an additional condition under which any fault set cannot contain all the neighbors of any node in a system. This study evaluated the conditional diagnosability for pancake graphs in the PMC model. First, several properties of pancake graphs were derived and, based on these properties, the conditional diagnosability of an n-dimensional pancake graph was shown to be 2 for \(n=3\) and \(8n-21\) for \(n\ge 4\).



中文翻译:

煎饼图:结构属性和条件可诊断性

由于多处理器系统的规模不断扩大,处理器故障诊断在衡量可靠性方面发挥了关键作用。许多著名的多处理器系统的可诊断性已被广泛研究。条件可诊断性是一种新的可诊断性度量,它限制了一个附加条件,在该附加条件下,任何故障集都不能包含系统中任何节点的所有邻居。本研究评估了 PMC 模型中煎饼图的条件可诊断性。首先,导出了 pancake 图的几个属性,并且基于这些属性,n维 pancake 图的条件可诊断性显示为 2 对于\(n=3\)\(8n-21\)对于\( n\ge 4\)

更新日期:2022-07-26
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