An energy conservation method for wireless sensor networks employing a blue noise spatial sampling technique

  • Authors:
  • Mark Perillo;Zeljko Ignjatovic;Wendi Heinzelman

  • Affiliations:
  • University of Rochester, Rochester, NY;University of Rochester, Rochester, NY;University of Rochester, Rochester, NY

  • Venue:
  • Proceedings of the 3rd international symposium on Information processing in sensor networks
  • Year:
  • 2004

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Abstract

In this work, we present a method for the selection of a subset of nodes in a wireless sensor network whose application is to reconstruct the image of a (spatially) bandlimited physical value (e.g., temperature). The selection method creates a sampling pattern based on blue noise masking and guarantees a near minimal number of activated sensors for a given signal-to-noise ratio. The selection method is further enhanced to guarantee that the sensor nodes with the least residual energy are the primary candidates for deselection, while enabling a tradeoff between sensor selection optimality and balanced load distribution. Simulation results show the effectiveness of these selection methods in improving signal-to-noise ratio and reducing the necessary number of active sensors compared with simpler selection approaches.