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Tandem: A Context-Aware Method for Spontaneous Clustering of Dynamic Wireless Sensor Nodes

  • Raluca Marin-Perianu
  • Clemens Lombriser
  • Paul Havinga
  • Hans Scholten
  • Gerhard Tröster
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4952)

Abstract

Wireless sensor nodes attached to everyday objects and worn by people are able to collaborate and actively assist users in their activities. We propose a method through which wireless sensor nodes organize spontaneously into clusters based on a common context. Provided that the confidence of sharing a common context varies in time, the algorithm takes into account a window-based history of believes. We approximate the behaviour of the algorithm using a Markov chain model and we analyse theoretically the cluster stability. We compare the theoretical approximation with simulations, by making use of experimental results reported from field tests. We show the tradeoff between the time history necessary to achieve a certain stability and the responsiveness of the clustering algorithm.

Keywords

Sensor Node Wireless Sensor Network Time History Root Node Communication Overhead 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Raluca Marin-Perianu
    • 1
  • Clemens Lombriser
    • 2
  • Paul Havinga
    • 1
  • Hans Scholten
    • 1
  • Gerhard Tröster
    • 2
  1. 1.Pervasive Systems GroupUniversity of TwenteThe Netherlands
  2. 2.Wearable Computing LabETH Zürich 

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