On Fault Isolation and Identification in t1/t1-Diagnosable Systems
IEEE Transactions on Computers
A Generalized Theory for System Level Diagnosis
IEEE Transactions on Computers
Topological Properties of Hypercubes
IEEE Transactions on Computers
Generalized Measures of Fault Tolerance with Application to N-Cube Networks
IEEE Transactions on Computers
Sequential Fault Occurrence and Reconfiguration in System Level Diagnosis
IEEE Transactions on Computers
A Characterization of t/s-Diagnosability and Sequential t-Diagnosability in Designs
IEEE Transactions on Computers
Diagnosabilities of Hypercubes Under the Pessimistic One-Step Diagnosis Strategy
IEEE Transactions on Computers
On Self-Diagnosable Multiprocessor Systems: Diagnosis by the Comparison Approach
IEEE Transactions on Computers
Diagnosis of t/(t +1)-Diagnosable Systems
SIAM Journal on Computing
On the generalized twisted cube
Information Processing Letters
On Diagnosability of Large Fault Sets in Regular Topology-Based Computer Systems
IEEE Transactions on Computers
Diagnosability of the Möbius Cubes
IEEE Transactions on Parallel and Distributed Systems
Diagnosability of Hypercubes and Enhanced Hypercubes under the Comparison Diagnosis Model
IEEE Transactions on Computers
Diagnosability of Crossed Cubes under the Comparison Diagnosis Model
IEEE Transactions on Parallel and Distributed Systems
Conditional Connectivity Measures for Large Multiprocessor Systems
IEEE Transactions on Computers
IEEE Transactions on Computers
The Crossed Cube Architecture for Parallel Computation
IEEE Transactions on Parallel and Distributed Systems
Conditional Diagnosability Measures for Large Multiprocessor Systems
IEEE Transactions on Computers
Diagnosabilities of Regular Networks
IEEE Transactions on Parallel and Distributed Systems
(t,k)-Diagnosis for Matching Composition Networks
IEEE Transactions on Computers
(t, k) - Diagnosis for Matching Composition Networks under the MM* Model
IEEE Transactions on Computers
A (4n-9)/3 diagnosis algorithm on n-dimensional cube network
Information Sciences: an International Journal
Hamiltonian laceability of bubble-sort graphs with edge faults
Information Sciences: an International Journal
Edge-pancyclicity and path-embeddability of bijective connection graphs
Information Sciences: an International Journal
On Fault Identification in Diagnosable Systems
IEEE Transactions on Computers
A Theory of Diagnosability of Digital Systems
IEEE Transactions on Computers
Fault Diagnosis in a Boolean n Cube Array of Microprocessors
IEEE Transactions on Computers
On conditional diagnosability of the folded hypercubes
Information Sciences: an International Journal
($t$,$k$)-Diagnosability of Multiprocessor Systems with Applications to Grids and Tori
SIAM Journal on Computing
On conditional diagnosability and reliability of the BC networks
The Journal of Supercomputing
A note about some properties of BC graphs
Information Processing Letters
Strongly Diagnosable Systems under the Comparison Diagnosis Model
IEEE Transactions on Computers
Conditional diagnosability of hypercubes under the comparison diagnosis model
Journal of Systems Architecture: the EUROMICRO Journal
The Strong Diagnosability of Regular Networks and Product Networks under the PMC Model
IEEE Transactions on Parallel and Distributed Systems
Conditional Edge-Fault Hamiltonicity of Matching Composition Networks
IEEE Transactions on Parallel and Distributed Systems
On the independent spanning trees of recursive circulant graphs G(cdm,d) with d2
Theoretical Computer Science
The Conditional Diagnosability of Hypercubes under the Comparison Model
ICIE '09 Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01
Conditional diagnosability of matching composition networks under the PMC model
IEEE Transactions on Circuits and Systems II: Express Briefs
(t, k)-Diagnosability for Regular Networks
IEEE Transactions on Computers
Conditional edge-fault-tolerant Hamiltonicity of dual-cubes
Information Sciences: an International Journal
The conditional diagnosability of crossed cubes under the comparison model
International Journal of Computer Mathematics
Diagnosability of Two-Matching Composition Networks under the MM{}^{\ast} Model
IEEE Transactions on Dependable and Secure Computing
Embedding meshes into twisted-cubes
Information Sciences: an International Journal
(t,k)-Diagnosis for Component-Composition Graphs under the MM* Model
IEEE Transactions on Computers
Conditional Diagnosability of Augmented Cubes under the PMC Model
IEEE Transactions on Dependable and Secure Computing
A fast fault-identification algorithm for bijective connection graphs using the PMC model
Information Sciences: an International Journal
Diagnosability of star graphs with missing edges
Information Sciences: an International Journal
The diagnosability of the matching composition network under the comparison diagnosis model
IEEE Transactions on Computers
IEEE Transactions on Computers
Conditional Diagnosability of Alternating Group Graphs
IEEE Transactions on Computers
The Conditional Diagnosability of k-Ary n-Cubes under the Comparison Diagnosis Model
IEEE Transactions on Computers
Hamiltonian properties of honeycomb meshes
Information Sciences: an International Journal
Adaptive system-level diagnosis for hypercube multiprocessors using a comparison model
Information Sciences: an International Journal
| Hi-index | 0.07 |
Diagnosability is a critical metric for determining the reliability of a multiprocessor system. In 2005, Lai et al. proposed a new measure for the fault diagnosis of a system, i.e., conditional diagnosability, in which it is assumed that at least one of the neighbors of an arbitrary node in the system is not faulty. In this paper, we obtain a sufficient condition for a class of networks, called Matching Composition Networks (MCNs), which are conditionally t-diagnosable under the MM^* model. Then, we apply the sufficient condition to show the conditional diagnosability of bijective connection (BC) networks. Finally, we show that the sufficient condition can be applied to networks other than BC networks.