A probabilistic method for fault diagnosis of multiprocessor systems

2003 ◽  
Author(s):  
S. Rangarajan ◽  
D. Fussell
Keyword(s):  
Fault Diagnosis ◽  
Probabilistic Method ◽  
Multiprocessor Systems

Optimal adaptive fault diagnosis for simple multiprocessor systems

Networks ◽  
1999 ◽  
Vol 34 (3) ◽  
pp. 206-214 ◽  
Author(s):  
Evangelos Kranakis ◽  
Andrzej Pelc ◽  
Anthony Spatharis
Keyword(s):  
Fault Diagnosis ◽  
Multiprocessor Systems

Adaptive Diagnosis of Hamiltonian Networks under the Comparison Model

2021 ◽  
pp. 2150015
Author(s):  
Wenjun Liu ◽  
Wenjun Li
Keyword(s):  
Fault Diagnosis ◽  
Upper Bound ◽  
Multiprocessor Systems ◽  
Major Goal ◽  
Comparison Model ◽  
A Value ◽  
Pmc Model ◽  
Diagnosis Algorithm ◽  
Test Outcomes

Adaptive diagnosis is an approach in which tests can be scheduled dynamically during the diagnosis process based on the previous test outcomes. Naturally, reducing the number of test rounds as well as the total number of tests is a major goal of an efficient adaptive diagnosis algorithm. The adaptive diagnosis of multiprocessor systems under the PMC model has been widely investigated, while adaptive diagnosis using comparison model has been independently discussed only for three networks, including hypercube, torus, and completely connected networks. In addition, adaptive diagnosis of general Hamiltonian networks is more meaningful than that of special graph. In this paper, the problem of adaptive fault diagnosis in Hamiltonian networks under the comparison model is explored. First, we propose an adaptive diagnostic scheme which takes five to six test rounds. Second, we derive a dynamic upper bound of the number of fault nodes instead of setting a value like normal. Finally, we present an algorithm such that at least one sequence obtained from cycle partition can be picked out and all nodes in this sequence can be identified based on the previous upper bound.

Intermittent fault diagnosis in multiprocessor systems

1992 ◽  
Vol 41 (11) ◽  
pp. 1430-1441 ◽  
Author(s):  
D.M. Blough ◽  
G.F. Sullivan ◽  
G.M. Masson
Keyword(s):  
Fault Diagnosis ◽  
Multiprocessor Systems ◽  
Intermittent Fault

Inter Processor Communication for Fault Diagnosis in Multiprocessor Systems

1994 ◽  
Vol 44 (2) ◽  
pp. 99-104 ◽  
Author(s):  
C. D. Malleswar ◽  
Ashok Jhunjhunwala
Keyword(s):  
Fault Diagnosis ◽  
Multiprocessor Systems

scholarly journals Two-Round Diagnosability Measures for Multiprocessor Systems

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Jiarong Liang ◽  
Qian Zhang ◽  
Changzhen Li
Keyword(s):  
Fault Diagnosis ◽  
Time Complexity ◽  
Multiprocessor System ◽  
Multiprocessor Systems ◽  
Pmc Model ◽  
Diagnosis Algorithm ◽  
Conditional Diagnosability ◽  
Novel Concept ◽  
Measure Index

In a multiprocessor system, as a key measure index for evaluating its reliability, diagnosability has attracted lots of attentions. Traditional diagnosability and conditional diagnosability have already been widely discussed. However, the existing diagnosability measures are not sufficiently comprehensive to address a large number of faulty nodes in a system. This article introduces a novel concept of diagnosability, called two-round diagnosability, which means that all faulty nodes can be identified by at most a one-round replacement (repairing the faulty nodes). The characterization of two-round t-diagnosable systems is provided; moreover, several important properties are also presented. Based on the abovementioned theories, for the n-dimensional hypercube Qn, we show that its two-round diagnosability is n2+n/2, which is n+1/2 times its classic diagnosability. Furthermore, a fault diagnosis algorithm is proposed to identify each node in the system under the PMC model. For Qn, we prove that the proposed algorithm is the time complexity of On2n.

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