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Geometric Distance Estimation for Sensor Networks and Unit Disk Graphs

Authors: Sándor Fekete, Alexander Kröller, Carsten Buschmann, and Stefan Fischer

Published in: Dagstuhl Seminar Proceedings, Volume 6481, Geometric Networks and Metric Space Embeddings (2007)


Abstract
We present an approach to estimating distances in sensor networks. It works by counting common neighbors, high values indicating closeness. Such distance estimates are needed in many self-localization algorithms. Other than many other approaches, ours does not rely on special equipment in the devices.

Cite as

Sándor Fekete, Alexander Kröller, Carsten Buschmann, and Stefan Fischer. Geometric Distance Estimation for Sensor Networks and Unit Disk Graphs. In Geometric Networks and Metric Space Embeddings. Dagstuhl Seminar Proceedings, Volume 6481, pp. 1-2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)


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@InProceedings{fekete_et_al:DagSemProc.06481.2,
  author =	{Fekete, S\'{a}ndor and Kr\"{o}ller, Alexander and Buschmann, Carsten and Fischer, Stefan},
  title =	{{Geometric Distance Estimation for Sensor Networks and Unit Disk Graphs}},
  booktitle =	{Geometric Networks and Metric Space Embeddings},
  pages =	{1--2},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{6481},
  editor =	{Joachim Gudmundsson and Rolf Klein and Giri Narasimhan and Michiel Smid and Alexander Wolff},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.06481.2},
  URN =		{urn:nbn:de:0030-drops-10282},
  doi =		{10.4230/DagSemProc.06481.2},
  annote =	{Keywords: Sensor networks, distance estimation, unit disk graphs.}
}
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