Tolerant identification with Euclidean balls

The concept of identifying codes was introduced by Karpovsky, Chakrabarty and Levitin in 1998. The identifying codes can be applied, for example, to sensor networks. In this article, we consider as sensors the set \documentclass{article}\usepackage{mathrsfs, amsmath, amssymb}\pagestyle{empty}\begin{document} $\mathbb{Z}^2$ \end{document} where one sensor can check its neighbors within Euclidean distance r. We construct tolerant identifying codes in this network that are robust against some changes in the neighborhood monitored by each sensor. We give bounds for the smallest density of a tolerant identifying code for general values of r. We also provide infinite families of values r with optimal such codes and study the case of small values of r. © 2012 Wiley Periodicals, Inc. NETWORKS, 2013

• Publication year

  2011

• Venue

  Networks

• Publication date

  2011-09-09

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1002/net.21472arXiv 1109.1913
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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