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Guanghui Guo

dblp:29/3560 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1998
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 50% Interconnection networks and networks-on-chip · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Interconnection networks and networks-on-chip › network topology › hypercubic networks
hypercube
0.011998
Fault Tolerance Measures for m-Ary n-Dimensional Hypercubes Based on Forbidden Faulty Sets · IEEE Trans. Computers 1998
Distributed systems › fault tolerance › resilience
network resilience
0.011998
Fault Tolerance Measures for m-Ary n-Dimensional Hypercubes Based on Forbidden Faulty Sets · IEEE Trans. Computers 1998

Methods — techniques the papers use, named apart from their topics

graph theory · 0.0
YearPublicationVenuePosition
1998 Fault Tolerance Measures for m-Ary n-Dimensional Hypercubes Based on Forbidden Faulty Sets
abstract
In this paper, we study fault tolerance measures for m-ary n-dimensional hypercubes based on the concept of forbidden faulty sets. In a forbidden faulty set, certain nodes cannot be faulty at the same time and this model can better reflect fault patterns in a real system than the existing ones. Specifically, we study the bounds of the minimum vertex cut set for m-ary n-dimensional hypercubes by requiring each node to have at least k healthy neighbors. Our result enhances and generalizes a result by Latifi et al. for binary hypercubes. Our study also shows that the corresponding result based on the traditional fault model (where k is zero) tends to underestimate network resilience of large networks such as m-ary n-dimensional hypercubes.
Jie Wu 0001, Guanghui Guo
IEEE Trans. Computers2