Neighborhood-Based Topology Recognition in Sensor Networks

  • S. P. Fekete
  • A. Kröller
  • D. Pfisterer
  • S. Fischer
  • C. Buschmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3121)


We consider a crucial aspect of self-organization of a sensor network consisting of a large set of simple sensor nodes with no location hardware and only very limited communication range. After having been distributed randomly in a given two-dimensional region, the nodes are required to develop a sense for the environment, based on a limited amount of local communication. We describe algorithmic approaches for determining the structure of boundary nodes of the region, and the topology of the region. We also develop methods for determining the outside boundary, the distance to the closest boundary for each point, the Voronoi diagram of the different boundaries, and the geometric thickness of the network. Our methods rely on a number of natural assumptions that are present in densely distributed sets of nodes, and make use of a combination of stochastics, topology, and geometry. Evaluation requires only a limited number of simple local computations.

ACM classification: C.2.1 Network architecture and design; F.2.2 Nonnumerical algorithms and problems; G.3 Probability and statistics

MSC classification: 68Q85, 68W15, 62E17


Sensor networks smart dust location awareness topology recognition neighborhood-based computation boundary recognition Voronoi regions geometric properties of sensor networks random distribution 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • S. P. Fekete
    • 1
  • A. Kröller
    • 1
  • D. Pfisterer
    • 2
  • S. Fischer
    • 2
  • C. Buschmann
    • 2
  1. 1.Department of Mathematical OptimizationBraunschweig University of TechnologyBraunschweigGermany
  2. 2.Institute of Operating Systems and Computer NetworksBraunschweig University of TechnologyBraunschweigGermany

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