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The Bin-Covering Technique for Thresholding Random Geometric Graph Properties

By S. Muthukrishnan and Gopal Pandurangan

Abstract

We study the emerging phenomenon of ad hoc, sensor-based communication networks. The communication is modeled by the random geometric graph model G(n, r, ℓ) where n points randomly placed within [0, ℓ] d form the nodes, and any two nodes that correspond to points at most distance r away from each other are connected. We study fundamental properties of G(n, r, ℓ) of interest: connectivity, coverage, and routing-stretch. Our main contribution is a simple analysis technique we call bin-covering that we apply uniformly to get (asymptotically) tight thresholds for each of these properties. Typically, in the past, random geometric graph analyses involved sophisticated methods from continuum percolation theory; on contrast, our bin-covering approach is discrete and very simple, yet it gives us tight threshold bounds. The technique also yields algorithmic benefits as illustrated by a simple local routing algorithm for finding paths with low stretch. Our specific results should also prove interesting to the networking community that has seen a recent increase in the study of random geometric graphs motivated by engineering ad hoc networks

Topics: Random geometric graphs, Thresholds, Sensor network models, Local algorithm, Coverage, Stretch, Connectivity
Year: 2005
OAI identifier: oai:CiteSeerX.psu:10.1.1.134.8298
Provided by: CiteSeerX
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