Coding and information theory (2nd ed.)
Coding and information theory (2nd ed.)
The connection machine
Locating faults in a constant number of parallel testing rounds
SPAA '89 Proceedings of the first annual ACM symposium on Parallel algorithms and architectures
Efficient Diagnosis of Multiprocessor Systems Under Probabilistic Models
IEEE Transactions on Computers
Fault diagnosis in a small constant number of parallel testing rounds
SPAA '93 Proceedings of the fifth annual ACM symposium on Parallel algorithms and architectures
Adaptive System-Level Diagnosis for Hypercube Multiprocessors
IEEE Transactions on Computers
IEEE Transactions on Computers
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Reliable Fault Diagnosis with Few Tests
Combinatorics, Probability and Computing
On Adaptive Fault Diagnosis for Multiprocessor Systems
ISAAC '01 Proceedings of the 12th International Symposium on Algorithms and Computation
A partitioning method for efficient system-level diagnosis
Journal of Systems and Software
Reducing the Number of Sequential Diagnosis Iterations in Hypercubes
IEEE Transactions on Computers
A fast pessimistic one-step diagnosis algorithm for hypercube multicomputer systems
Journal of Parallel and Distributed Computing
A (4n-9)/3 diagnosis algorithm on n-dimensional cube network
Information Sciences: an International Journal
A fast diagnosis algorithm for locally twisted cube multiprocessor systems under the MM* model
Computers & Mathematics with Applications
Three-round adaptive diagnosis in binary n-cubes
ISAAC'04 Proceedings of the 15th international conference on Algorithms and Computation
Adaptive system-level diagnosis for hypercube multiprocessors using a comparison model
Information Sciences: an International Journal
| Hi-index | 14.99 |
We consider the problem of adaptive fault diagnosis in hypercube multiprocessor systems. Processors perform tests on one another and later tests can be scheduled on the basis of previous test results. Fault-free testers correctly identify the fault status of tested processors, while faulty testers can give arbitrary test results. The goal is to identify correctly the status of all processors, assuming that the number of faults does not exceed the hypercube dimension. We propose an adaptive diagnosis algorithm whose efficiency is drastically better than that of any previously known strategies. While the worst-case number of tests for any of them exceeds $2^n \log n$ for an $n{\hbox{-}}{\rm dimensional}$ hypercube, our method uses at most $2^n + 3n/2$ tests in the worst case. We can also modify our algorithm to improve the number of testing rounds. By slightly increasing the number of tests to $2^n + (n+1)^2$ (still a much better performance than $2^n \log n$), we can carry out diagnosis in at most 11 rounds in the worst case (as opposed to over $n$ rounds in the best previously known strategy).