PMC model
The Preparata–Metze–Chien model, or PMC model, is a foundational model in system-level fault diagnosis, used in the analysis and design of multiprocessor systems. It was introduced in 1967 by Franco P. Preparata, Gernot Metze, and Robert Tienwen Chien in the context of improving the fault tolerance of large-scale distributed systems.
In the PMC model, the system is modeled as a directed graph, where each vertex represents a processor and a directed edge from vertex u to v indicates that processor u can test processor v. A key assumption of the model is that only fault-free processors produce reliable test results. The collection of all test outcomes is called a syndrome, which is analyzed to determine the identity of faulty nodes.
A system is said to be t-diagnosable under the PMC model if any faulty set of up to t processors can be uniquely identified from the syndrome. The diagnosability of a graph is the largest such t.
The model continues to play a central role in research on reliable computing and has influenced a wide range of diagnostic algorithms and network design methodologies.
See also
References
- Preparata, Franco P.; Metze, Gernot; Chien, Robert T. (1967). "On the Connection Assignment Problem of Diagnosable Systems". IEEE Transactions on Electronic Computers. EC-16 (6): 848–854. doi:10.1109/PGEC.1967.264748. hdl:2142/74464.
This article "PMC model" is from Wikipedia. The list of its authors can be seen in its historical and/or the page Edithistory:PMC model. Articles copied from Draft Namespace on Wikipedia could be seen on the Draft Namespace of Wikipedia and not main one.
