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可诊断度是衡量一个互连网络可靠性的重要指标,用来评估当系统中某些顶点出现故障时该系统可以准确找出故障顶点的能力.PMC模型是并行计算机系统中的一种经典的可诊断模型,被广泛地应用于系统诊断,目前已有大量的基于PMC模型的系统诊断性质研究.类超立方体是一种重要的网络拓扑结构,有很多很好的性质,其中超立方体网络在实际中得到了广泛应用.研究者们针对类超立方体网络存在坏边或者硬故障顶点时系统可诊断度进行了研究,对同时存在两种故障情形下的可诊断度还没有相关研究.设是一个-维类超立方体网络,本文证明对于坏边和硬故障顶点的集合S,若|S|≤n-1且,则H_n-S在PMC模型下的系统可诊断度是δ(H_n-S),其中δ(H_n-S)表示H_n-S的最小顶点度数.
Diagnostic degree is an important index to measure the reliability of an interconnection network and is used to evaluate the ability of the system to accurately find fault vertices when some vertices in the system fail.PMC model is a classic Diagnostic models are widely used in system diagnostics, and there are a lot of studies on the properties of system diagnostics based on PMC model.Classic hypercube is an important network topology with many good properties, including hypercube network And has been widely used in practice.Researchers have studied the diagnosticability of the system in the presence of a bad edge or hard fault vertex in a class of hypercube networks and have not done any research on the diagnostability under the simultaneous existence of two fault scenarios. A-dimensional hypercube network, the paper proves that for a set S of bad edges and hard fault vertices, the system diagnostic degree of H_n-S under the PMC model is δ (H_n-S ), Where δ (H_n-S) denotes the minimum vertex degree of H_n-S.