A fault identification algorithm for ti-diagnosable systems
IEEE Transactions on Computers - The MIT Press scientific computation series
The Comparison Approach to Multiprocessor Fault Diagnosis
IEEE Transactions on Computers
Probabilistic multiprocessor and multicomputer diagnosis
Probabilistic multiprocessor and multicomputer diagnosis
Fault detection and diagnosis in multiprocessor systems
Fault detection and diagnosis in multiprocessor systems
Automated Rule-Based Diagnosis through a Distributed Monitor System
IEEE Transactions on Dependable and Secure Computing
| Hi-index | 0.00 |
This paper addresses the distributed self-diagnosis of a multiprocessor/multicomputersystem based on fault syndromes formed by comparison testing. The authors show thatby using multiple fault syndromes, it is possible to achieve significantly better diagnosisthan by using a single fault syndrome, even when the amount of time devoted to testingis the same. They derive a multiple syndrome diagnosis algorithm that in terms of thelevel of diagnostic accuracy achieved, is globally suboptimal, but optimal among alldiagnosis algorithms of a certain type to be defined. The diagnosis algorithm producesgood results, even with sparse interconnection networks and interprocessor tests withlow fault coverage. It is also proven that the diagnosis algorithm produces 100% correctdiagnosis as N, the number of nodes in the system, approaches /spl infin/, provided thatthe interconnection network has connectivity greater than or equal to 2 and that thenumber of syndromes produced grows faster than log N. This solution and anothermultiple syndrome diagnosis solution by Fussell and Rangarajan (1989) are comparatively evaluated, both analytically and with simulations.