Efficient distributed algorithms for self testing of multiple processor systems

Multiple processor systems allow both highly reliable and highly fast service. Distributed self-test algorithms that attempt to improve both the reliability and the performance of these systems are proposed. In these algorithms, reliability is improved by considering the distributed mode of control...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE transactions on computers Ročník 41; číslo 11; s. 1397 - 1409
Hlavní autoři: Hosseini, S.H., Jamal, N.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY IEEE 01.11.1992
Institute of Electrical and Electronics Engineers
Témata:
Applied sciences
Automatic testing
Built-in self-test
Communication channels
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Distributed algorithms
Distributed computing
Distributed control
Exact sciences and technology
Fault diagnosis
Performance evaluation
Process control
Software
System testing
Multiprocessor
Fault tolerance
Test
Spanning tree
Computer system
Distributed system
System reliability
Synchronization
Time complexity
Fault diagnostic
Non directed graph
Reconfiguration
ISSN:0018-9340
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Multiple processor systems allow both highly reliable and highly fast service. Distributed self-test algorithms that attempt to improve both the reliability and the performance of these systems are proposed. In these algorithms, reliability is improved by considering the distributed mode of control and assigning processors to test each other periodically for the diagnosis and isolation of the faulty processors and interprocessor links. Meanwhile, performance is improved by considering a dynamic testing strategy and minimizing testing overhead by reducing the number of tests performed on each processor. Simulation results show the effectiveness of the algorithms.< >
Bibliografie:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0018-9340
DOI:10.1109/12.177310