Managing evolving shapes in sensor networks

Besim Avci, Goce Trajcevski, Peter I Scheuermann

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This work addresses the problem of efficient distributed detection and tracking of mobile and evolving/deformable spatial shapes in Wireless Sensor Networks (WSN). The shapes correspond to contiguous regions bounding the locations of sensors in which the readings of the sensors satisfy a particular threshold-based criterion related to the values of a physical phenomenon that they measure. We formalize the predicates representing the shapes in such settings and present detection algorithms. In addition, we provide a light-weight protocol and aggregation methods for energy-efficient distributed execution of those algorithms. Another contribution of this work is that we developed efficient techniques for detecting a co-occurrence of shapes within a given proximity from each other. Our experiments demonstrate that, when compared to the centralized techniques-which is, predicates being detected in a dedicated sink-as well as distributed periodic contours construction, our methodologies yield signi ficant energy/communication savings.

Original languageEnglish (US)
Title of host publicationSSDBM 2014 - Proceedings of the 26th International Conference on Scientific and Statistical Database Management
PublisherAssociation for Computing Machinery
ISBN (Print)9781450327220
DOIs
StatePublished - Jan 1 2014
Event26th International Conference on Scientific and Statistical Database Management, SSDBM 2014 - Aalborg, Denmark
Duration: Jun 30 2014Jul 2 2014

Other

Other26th International Conference on Scientific and Statistical Database Management, SSDBM 2014
CountryDenmark
CityAalborg
Period6/30/147/2/14

Keywords

  • Evolving shapes
  • Spatio-temporal events
  • Wireless sensor networks
  • WSN

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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  • Cite this

    Avci, B., Trajcevski, G., & Scheuermann, P. I. (2014). Managing evolving shapes in sensor networks. In SSDBM 2014 - Proceedings of the 26th International Conference on Scientific and Statistical Database Management [22] Association for Computing Machinery. https://doi.org/10.1145/2618243.2618264