三次哈密顿图最优自适应故障诊断

Toru Araki
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引用次数: 5

摘要

研究了用三次哈密顿图建模的多处理器系统的自适应故障诊断问题。系统中的每个节点都可能处于故障或无故障状态,故障诊断的目的是正确识别所有节点的故障或无故障状态。为了实现这一目标,每个节点测试其邻居并输出测试结果。如果测试节点无故障,则测试节点始终输出正确的测试结果,如果测试节点故障,则测试结果不可信。给出了三次哈密顿图在3轮测试中被采用诊断的充分条件,即每个节点在每轮测试中最多参与一次测试。这是测试轮次的最佳数量。满足这个条件的这类图包含了几个重要的网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal adaptive fault diagnosis of cubic Hamiltonian graphs
We study the problem of adaptive fault diagnosis for multiprocessor systems modeled by cubic Hamiltonian graphs. Each node in a system is either faulty or fault-free, and the aim of fault diagnosis is to identify correctly faulty/fault-free status of all nodes. In order to achieve it, each node tests their neighbors and output the results of tests. If the test node is fault-free, it always outputs correct test results, but if the test node is faulty, the result of the test cannot be trusted. We give a sufficient condition for a cubic Hamiltonian graph to be adoptively diagnosed in 3 testing rounds, provided that each node participates in at most one test of each round. It is the optimal number of testing rounds. The class of these graphs that satisfy this condition contains several important networks.
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