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Discrete Applied Mathematics
Article
License: Elsevier Non-Commercial
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Discrete Applied Mathematics
Article . 2001
License: Elsevier Non-Commercial
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Discrete Applied Mathematics
Article . 2001 . Peer-reviewed
License: Elsevier Non-Commercial
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Part of book or chapter of book . 1999 . Peer-reviewed
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Fixed-Parameter Complexity of λ-Labelings

Authors: Fiala, Jiřı́; Kloks, Ton; Kratochvı́l, Jan;

Fixed-Parameter Complexity of λ-Labelings

Abstract

AbstractA λ-labeling of a graph G is an assignment of labels from the set {0,…,λ} to the vertices of G such that vertices at distance of at most two get different labels and adjacent vertices get labels which are at least two apart. We study the minimum value λ=λ(G) such that G admits a λ-labeling. We show that for every fixed value k⩾4 it is NP-complete to determine whether λ(G)⩽k. We further investigate this problem for sparse graphs (k-almost trees), extending the already known result for ordinary trees. In a generalization of this problem we wish to find a labeling such that vertices at distance two are assigned labels that differ by at least q and the labels of adjacent vertices differ by at least p. We denote the minimum λ that allows such a labeling by L(G;p,q). We show several hardness results for L(G;p,q) including that for any p>q⩾1 there is a λ=λ(p,q) such that deciding if L(G;p,q)⩽λ is NP-complete, and that for p⩾2q, this decision is NP-complete for every λ⩾λ(p,q).

Related Organizations
Keywords

Applied Mathematics, Graph cover, Discrete Mathematics and Combinatorics, Channel assignment, Fixed-parameter complexity, Graph labeling

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
101
Top 10%
Top 1%
Top 10%
hybrid