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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.

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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.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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DOI: 10.4230/DagSemProc.05361.6

Deterministic boundary recongnition and topology extraction for large sensor networks

Authors: Sándor Fekete, Alexander Kröller, Dennis Pfisterer, and Stefan Fischer

Published in: Dagstuhl Seminar Proceedings, Volume 5361, Algorithmic Aspects of Large and Complex Networks (2006)

Abstract

We present a new framework for the crucial challenge of self-organization of a large sensor network. The basic scenario can be described as follows: Given a large swarm of immobile sensor nodes that have been scattered in a polygonal region, such as a street network. Nodes have no knowledge of size or shape of the environment or the position of other nodes. Moreover, they have no way of measuring coordinates, geometric distances to other nodes, or their direction. Their only way of interacting with other nodes is to send or to receive messages from any node that is within communication range. The objective is to develop algorithms and protocols that allow self-organization of the swarm into large-scale structures that reflect the structure of the street network, setting the stage for global routing, tracking and guiding algorithms. Our algorithms work in two stages: boundary recognition and topology extraction. All steps are strictly deterministic, yield fast distributed algorithms, and make no assumption on the distribution of nodes in the environment, other than sufficient density.

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Sándor Fekete, Alexander Kröller, Dennis Pfisterer, and Stefan Fischer. Deterministic boundary recongnition and topology extraction for large sensor networks. In Algorithmic Aspects of Large and Complex Networks. Dagstuhl Seminar Proceedings, Volume 5361, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{fekete_et_al:DagSemProc.05361.6,
  author =	{Fekete, S\'{a}ndor and Kr\"{o}ller, Alexander and Pfisterer, Dennis and Fischer, Stefan},
  title =	{{Deterministic boundary recongnition and topology extraction for large sensor networks}},
  booktitle =	{Algorithmic Aspects of Large and Complex Networks},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{5361},
  editor =	{Stefano Leonardi and Friedhelm Meyer auf der Heide and Dorothea Wagner},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05361.6},
  URN =		{urn:nbn:de:0030-drops-5632},
  doi =		{10.4230/DagSemProc.05361.6},
  annote =	{Keywords: Distributed algorithms, sensor networks, boundary recognition, topology extraction}
}

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Documents authored by Kröller, Alexander

Geometric Distance Estimation for Sensor Networks and Unit Disk Graphs

Abstract

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Deterministic boundary recongnition and topology extraction for large sensor networks

Abstract

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