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Geometric spanner networks

By: Narasimhan,Giri.
Contributor(s): Smid, Michiel.
Publisher: Cambridge Cambridge University Press 2007Description: xv, 500 p. ill. 26 cm.ISBN: 9780521815130.Subject(s): Computer Algorithms | Trees - Graph Theory | Data Processing | Geometry | Computer programming - Open Source | Software Development and​ Engineering | Computer science | Science - MathematicsDDC classification: 005.1 Summary: Aimed at an audience of researchers and graduate students in computational geometry and algorithm design, this hook uses the Geometric spanner Network Problem to showcase a number of useful algorithmic techniques, data structure strategies, and geometric analysis techniques with many applications, practical and theoretical.". "The authors present rigorous descriptions of the main algorithms and their analyses for different variations of the Geometric Spanner Network Problem. Although the basic ideas behind most of these algorithms are intuitive, very few are easy to describe and analyze, tor most of the algorithms, nontrivial data structures need to be designed, and nontrivial techniques need to he developed in order for analysis to take place. Still, there are several basic principle's and results that are used throughout the book. One of the most important is the powerful well-separated pair decomposition. This decomposition is used as a starting point for several of the spanner constructions.
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Books 005.1 NAR (Browse shelf) Available 032111

Aimed at an audience of researchers and graduate students in computational geometry and algorithm design, this hook uses the Geometric spanner Network Problem to showcase a number of useful algorithmic techniques, data structure strategies, and geometric analysis techniques with many applications, practical and theoretical.".
"The authors present rigorous descriptions of the main algorithms and their analyses for different variations of the Geometric Spanner Network Problem. Although the basic ideas behind most of these algorithms are intuitive, very few are easy to describe and analyze, tor most of the algorithms, nontrivial data structures need to be designed, and nontrivial techniques need to he developed in order for analysis to take place. Still, there are several basic principle's and results that are used throughout the book. One of the most important is the powerful well-separated pair decomposition. This decomposition is used as a starting point for several of the spanner constructions.

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