Self-Implicating Structures for Diagnosable Systems
IEEE Transactions on Computers
IEEE Transactions on Computers - The MIT Press scientific computation series
Algorithms for finding diagnosability level and t-diagnosis in a network of processors
ACM '82 Proceedings of the ACM '82 conference
The complexity of system-level fault diagnosis and diagnosability
The complexity of system-level fault diagnosis and diagnosability
The consensus problem in fault-tolerant computing
ACM Computing Surveys (CSUR)
Sequentially t-Diagnosable Systems: A Characterization and Its applications
IEEE Transactions on Computers - Special issue on fault-tolerant computing
IEEE Transactions on Computers
A flexible formal framework for masking/demasking faults
Information Sciences—Informatics and Computer Science: An International Journal
Worst-Case Diagnosis Completeness in Regular Graphs under the PMC Model
IEEE Transactions on Computers
Efficient Fault Identification of Diagnosable Systems under the Comparison Model
IEEE Transactions on Computers
A Framework for Identifying Compromised Nodes in Wireless Sensor Networks
ACM Transactions on Information and System Security (TISSEC)
International Journal of Parallel, Emergent and Distributed Systems
One-step t-fault diagnosis for hypermesh optical interconnection multiprocessor systems
Journal of Systems and Software
Fault diagnosis for hypercube-like networks
AICT'11 Proceedings of the 2nd international conference on Applied informatics and computing theory
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Systems composed of many processing units can use these units to help perform self-diagnosis. An algorithm is presented that performs this type of diagnosis for the system-level fault model. The time complexity of the algorithm is O(t鲁+ |E|), where |E| is the number of tests and t is the number of allowed faults. When t is small relative to the total number of system components n, this is the tightest known time bound; when t is O(n/sup 5/6/) this is the best bound.