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https://dx.doi.org/10.48550/ar...
Article . 2020
License: CC BY
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Book Embeddings of k-Map Graphs

Authors: Franz J. Brandenburg;

Book Embeddings of k-Map Graphs

Abstract

A map is a partition of the sphere into regions that are labeled as countries or holes. The vertices of a map graph are the countries of a map. There is an edge if and only if the countries are adjacent and meet in at least one point. For a k-map graph, at most k countries meet in a point. A graph is k-planar if it can be drawn in the plane with at most k crossings per edge. A p-page book embedding of a graph is a linear ordering of the vertices and an assignment of the edges to p pages, so that there is no conflict for edges assigned to the same page. The minimum number of pages is the book thickness of a graph, also known as stack number or page number. We show that every k-map graph has a book embedding in $6\lfloor k/2 \rfloor+5$ pages, which, for n-vertex graphs, can be computed in O(kn) time from its map. Our result improves the best known upper bound. Towards a lower bound, it is shown that some k-map graphs need $\lfloor 3k/4 \rfloor$ pages. In passing, we obtain an improved upper bound of eleven pages for 1-planar graphs, which are subgraphs of 4-map graphs, and of 17 pages for optimal 2-planar graphs.

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Keywords

Computational Geometry (cs.CG), FOS: Computer and information sciences, 68R10, Computer Science - Computational Geometry, G.2.2

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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
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