An Efficient Algorithm for Identifying the Most Likely Fault Set in a Probabilistically Diagnosable System

Dahbura,

doi:10.1109/tc.1986.1676769

Cited by 13 publications

(2 citation statements)

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“…It has been argued that the worst-case scenario often fails to reflect realistic diagnosis situations. As an alternative, various probabilistic models were proposed (see [6], [7], [8], [9], [15], [16], [19], [20]). Instead of imposing an upper bound on the number of faulty processors and assuming their worstcase location, an a priori failure probability, independent for each processor, is assumed in these models.…”

Section: Introductionmentioning

confidence: 99%

“…Instead of imposing an upper bound on the number of faulty processors and assuming their worstcase location, an a priori failure probability, independent for each processor, is assumed in these models. Diagnosis is then restricted to sets of faulty processors of sufficiently high a priori probability [15], in which case it can be performed unambiguously [9], or is done in general and has a high probability of correctness (see [5], [6], [7], [8], [16], [19], [20]).…”

Section: Introductionmentioning

confidence: 99%

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Reliable Fault Diagnosis with Few Tests

Pełc

Upfal

1998

Combinator. Probab. Comp.

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We consider the problem of fault diagnosis in multiprocessor systems. Processors perform tests on one another: fault-free testers correctly identify the fault status of tested processors, while faulty testers can give arbitrary test results. Processors fail independently with constant probability p < 1/2 and the goal is to identify correctly the status of all processors, based on the set of test results. For 0 < q < 1, q-diagnosis is a fault diagnosis algorithm whose probability of error does not exceed q. We show that the minimum number of tests to perform q-diagnosis for n processors is Θ(n log 1 q ) in the nonadaptive case and n + Θ(log 1 q ) in the adaptive case. We also investigate q-diagnosis algorithms that minimize the maximum number of tests performed by, and performed on, processors in the system, constructing testing schemes in which each processor is involved in very few tests. Our results demonstrate that the flexibility yielded by adaptive testing permits a significant saving in the number of tests for the same reliability of diagnosis.

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