Energy-efficient image transmission in sensor networks

  • Authors:
  • Vincent Lecuire;Cristian Duran-Faundez;Nicolas Krommenacker

  • Affiliations:
  • Centre de Recherche en Automatique de Nancy (CRAN UMR 7039), Nancy-Universite, CNRS, Faculte des Sciences et Techniques, BP 239, F-54506 Vandoeuvre-les-Nancy Cedex, France.;Centre de Recherche en Automatique de Nancy (CRAN UMR 7039), Nancy-Universite, CNRS, Faculte des Sciences et Techniques, BP 239, F-54506 Vandoeuvre-les-Nancy Cedex, France.;Centre de Recherche en Automatique de Nancy (CRAN UMR 7039), Nancy-Universite, CNRS, Faculte des Sciences et Techniques, BP 239, F-54506 Vandoeuvre-les-Nancy Cedex, France

  • Venue:
  • International Journal of Sensor Networks
  • Year:
  • 2008

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Abstract

In this paper, we propose two image transmission schemes driven by energy efficiency considerations in order to be suitable for Wireless Sensor Networks (WSNs). The first one is an open-loop image transmission scheme while the second one is closed-loop. Both schemes are based on wavelet image transform and semi-reliable transmission to achieve energy conservation. Wavelet image transform provides data decomposition in multiple levels of resolution, so the image can be divided into packets with different priorities. Semi-reliable transmission enables priority-based packet discarding by intermediate nodes according to their battery's state-of-charge. Such an image transmission approach provides a graceful trade-off between the image quality played out and the sensor nodes' lifetime. An analytical study in terms of dissipated energy is performed to compare our two schemes to a fully reliable image transmission scheme. Since image processing is computationally intensive and operates on a large data set, the cost of the wavelet image transform is considered in the energy consumption analysis. Results show up to 70% and 90% reductions in energy consumption with the open-loop and closed-loop schemes, respectively, compared to a non-energy-aware one, with a guarantee for the image quality to be lower-bounded.