Geometric Spanner Networks

Aimed at an audience of researchers and graduate students in computational geometry and algorithm design, this book 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. Though the basic ideas behind most of these algorithms are intuitive, very few are easy to describe and analyze. For most of the algorithms, nontrivial data structures need to be designed, and nontrivial techniques need to be developed in order for analysis to take place. Still, there are several basic principles 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.

Rigorous descriptions and analyses of the main algorithms for different variations of the Geometric Spanner Network Problem.

Giri Narasimhan earned a B.Tech. in Electrical Engineering from the Indian Institute of Technology in Mumbai, India, and a Ph.D. in Computer Science from the University of Wisconsin in Madison, Wisconsin, USA. He was a member of the faculty at the University of Memphis, and is currently at Florida International University.

Michiel Smid received a M.Sc. degree in Mathematics from the University of Technology in Eidenhoven and a Ph.D. degree in Computer Science from the University of Amsterdam. He has held teaching positions at the Max-Planck-Institute for Computer Science in Saarbrucken, King's College in London, and the University of Magdenburg. Since 2001, he has been at Carleton University, where he is currently a professor of Computer Science.