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Title: Coloring geographical threshold graphs

Abstract

We propose a coloring algorithm for sparse random graphs generated by the geographical threshold graph (GTG) model, a generalization of random geometric graphs (RGG). In a GTG, nodes are distributed in a Euclidean space, and edges are assigned according to a threshold function involving the distance between nodes as well as randomly chosen node weights. The motivation for analyzing this model is that many real networks (e.g., wireless networks, the Internet, etc.) need to be studied by using a 'richer' stochastic model (which in this case includes both a distance between nodes and weights on the nodes). Here, we analyze the GTG coloring algorithm together with the graph's clique number, showing formally that in spite of the differences in structure between GTG and RGG, the asymptotic behavior of the chromatic number is identical: {chi}1n 1n n / 1n n (1 + {omicron}(1)). Finally, we consider the leading corrections to this expression, again using the coloring algorithm and clique number to provide bounds on the chromatic number. We show that the gap between the lower and upper bound is within C 1n n / (1n 1n n){sup 2}, and specify the constant C.

Authors:
 [1];  [1];  [2]
  1. Los Alamos National Laboratory
  2. EINDHOVEN UNIV. OF TECH
Publication Date:
Research Org.:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
956667
Report Number(s):
LA-UR-08-08014; LA-UR-08-8014
Journal ID: ISSN 1365--8050; TRN: US201016%%2352
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Conference
Resource Relation:
Journal Volume: Vol. 12 no. 3; Journal Issue: Graph and Algorithms; Conference: Analco Soda ; January 2, 2009 ; New York, NY
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS; ALGORITHMS; COMPUTERIZED SIMULATION; COMPUTER NETWORKS; CORRECTIONS; DISTANCE; EUCLIDEAN SPACE; FUNCTIONS; INTERNET

Citation Formats

Bradonjic, Milan, Percus, Allon, and Muller, Tobias. Coloring geographical threshold graphs. United States: N. p., 2008. Web. doi:10.46298/dmtcs.497.
Bradonjic, Milan, Percus, Allon, & Muller, Tobias. Coloring geographical threshold graphs. United States. https://doi.org/10.46298/dmtcs.497
Bradonjic, Milan, Percus, Allon, and Muller, Tobias. 2008. "Coloring geographical threshold graphs". United States. https://doi.org/10.46298/dmtcs.497. https://www.osti.gov/servlets/purl/956667.
@article{osti_956667,
title = {Coloring geographical threshold graphs},
author = {Bradonjic, Milan and Percus, Allon and Muller, Tobias},
abstractNote = {We propose a coloring algorithm for sparse random graphs generated by the geographical threshold graph (GTG) model, a generalization of random geometric graphs (RGG). In a GTG, nodes are distributed in a Euclidean space, and edges are assigned according to a threshold function involving the distance between nodes as well as randomly chosen node weights. The motivation for analyzing this model is that many real networks (e.g., wireless networks, the Internet, etc.) need to be studied by using a 'richer' stochastic model (which in this case includes both a distance between nodes and weights on the nodes). Here, we analyze the GTG coloring algorithm together with the graph's clique number, showing formally that in spite of the differences in structure between GTG and RGG, the asymptotic behavior of the chromatic number is identical: {chi}1n 1n n / 1n n (1 + {omicron}(1)). Finally, we consider the leading corrections to this expression, again using the coloring algorithm and clique number to provide bounds on the chromatic number. We show that the gap between the lower and upper bound is within C 1n n / (1n 1n n){sup 2}, and specify the constant C.},
doi = {10.46298/dmtcs.497},
url = {https://www.osti.gov/biblio/956667}, journal = {},
issn = {1365--8050},
number = Graph and Algorithms,
volume = Vol. 12 no. 3,
place = {United States},
year = {Tue Jan 01 00:00:00 EST 2008},
month = {Tue Jan 01 00:00:00 EST 2008}
}

Conference:
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