EFFICIENT DIAGNOSIS OF MULTIPROCESSOR SYSTEMS UNDER PROBABILISTIC MODELS

被引：44

作者：

BLOUGH, DM ^{[1
]}

SULLIVAN, GF ^{[1
]}

MASSON, GM ^{[1
]}

机构：

[1] JOHNS HOPKINS UNIV, DEPT COMP SCI, BALTIMORE, MD 21218 USA

来源：

IEEE TRANSACTIONS ON COMPUTERS | 1992年 / 41卷 / 09期

关键词：

ALGORITHMS; FAULT DIAGNOSIS; HYPERCUBE; MULTIPROCESSOR SYSTEMS; PERMANENT FAULTS; PROBABILISTIC MODELS;

D O I：

10.1109/12.165394

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, the problem of fault diagnosis in multiprocessor systems is considered under a probabilistic fault model. This work focuses on minimizing the number of tests that must be conducted in order to correctly diagnose the state of every processor in the system with high probability. A diagnosis algorithm that can correctly diagnose the state of every processor with probability approaching one in a class of systems performing slightly greater than a linear number of tests is presented. A nearly matching lower bound on the number of tests required to achieve correct diagnosis in arbitrary systems is also proven. Lower and upper bounds on the number of tests required for regular systems are also presented. A class of regular systems which includes hypercubes is shown to be correctly diagnosable with high probability. In all cases, the number of tests required under this probabilistic model is shown to be significantly less than under a bounded-size fault set model. Because the number of tests that must be conducted is a measure of the diagnosis overhead, these results represent a dramatic improvement in the performance of system-level diagnosis techniques.

引用

页码：1126 / 1136

页数：11

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