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Anti-k-labeling of graphs

Anti-\(k\)-labeling of graphs
Authors: Xiaxia Guan; Shurong Zhang; Rong-Hua Li; Lin Chen 0002; Weihua Yang;

Anti-k-labeling of graphs

Abstract

It is well known that the labeling problems of graphs arise in many (but not limited to) networking and telecommunication contexts. In this paper we introduce the anti-$k$-labeling problem of graphs which we seek to minimize the similarity (or distance) of neighboring nodes. For example, in the fundamental frequency assignment problem in wireless networks where each node is assigned a frequency, it is usually desirable to limit or minimize the frequency gap between neighboring nodes so as to limit interference. Let $k\geq1$ be an integer and $��$ is a labeling function (anti-$k$-labeling) from $V(G)$ to $\{1,2,\cdots,k\}$ for a graph $G$. A {\em no-hole anti-$k$-labeling} is an anti-$k$-labeling using all labels between 1 and $k$. We define $w_��(e)=|��(u)-��(v)|$ for an edge $e=uv$ and $w_��(G)=\min\{w_��(e):e\in E(G)\}$ for an anti-$k$-labeling $��$ of the graph $G$. {\em The anti-$k$-labeling number} of a graph $G$, $mc_k(G)$ is $\max\{w_��(G): ��\}$. In this paper, we first show that $mc_k(G)=\lfloor \frac{k-1}{��-1}\rfloor$, and the problem that determines $mc_k(G)$ of graphs is NP-hard. We mainly obtain the lower bounds on no-hole anti-$n$-labeling number for trees, grids and $n$-cubes.

15pages

Related Organizations
Keywords

Graph labelling (graceful graphs, bandwidth, etc.), Coloring of graphs and hypergraphs, FOS: Mathematics, Mathematics - Combinatorics, channel assignment problem, Combinatorics (math.CO)

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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!
1
Average
Average
Average
Green