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.
@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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