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Best and worst case permutations for random online domination of the path

Authors: Dewitt, Jonathan; Coscia, Christopher; Yang, Fan; Zhang, Yiguang;

Best and worst case permutations for random online domination of the path

Abstract

We study a randomized algorithm for graph domination, by which, according to a uniformly chosen permutation, vertices are revealed and added to the dominating set if not already dominated. We determine the expected size of the dominating set produced by the algorithm for the path graph $P_n$ and use this to derive the expected size for some related families of graphs. We then provide a much-refined analysis of the worst and best cases of this algorithm on $P_n$ and enumerate the permutations for which the algorithm has the worst-possible performance and best-possible performance. The case of dominating the path graph has connections to previous work of Bouwer and Star, and of Gessel on greedily coloring the path.Comment: 13 pages, 1 figure

Country
United States
Keywords

Permutations, words, matrices, path graphs, mathematics - combinatorics, permutations, Randomized algorithms, random algorithms, graph domination, Vertex subsets with special properties (dominating sets, independent sets, cliques, etc.), asymptotics, QA1-939, FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), Mathematics

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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!
0
Average
Average
Average
Green
Published in a Diamond OA journal