Formalizes linear, geometric and stochastic allocation strategies for HyperX networks and reports that the non-convex Diagonal strategy outperforms others in experiments due to partition bandwidth and switch locality.
Revisiting the outer-weakly convex domination number in graph products
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Let $G = (V, E)$ be a simple undirected connected graph. A set $C \subseteq V(G)$ is weakly convex in $G$ if for every two vertices $u,v$ in $G$, there exists a $u-v$ geodesic whose vertices are in $C$. A set $C \subseteq V$ is an outer-weakly convex dominating set if every vertex not in $C$ is adjacent to some vertex in $C$ and the set $V(G)\setminus C$ is weakly convex in $G$. The outer-weakly convex domination number of graph $G$, denoted by $\widetilde{ \gamma}_{wcon}(G)$, is the minimum cardinality of an outer-weakly convex dominating set of graph $G$. In this paper, we determine the outer-weakly convex domination number of two graphs under the Cartesian, strong and lexicographic products, and discuss some important combinatorial findings.
fields
cs.DC 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
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Resource Allocation in HyperX Networks
Formalizes linear, geometric and stochastic allocation strategies for HyperX networks and reports that the non-convex Diagonal strategy outperforms others in experiments due to partition bandwidth and switch locality.