An energy conservation method for wireless sensor networks employing a blue noise spatial sampling technique
- 26 April 2004
- conference paper
- Published by Association for Computing Machinery (ACM)
- p. 116-123
- https://doi.org/10.1145/984622.984640
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.Keywords
This publication has 15 references indexed in Scilit:
- Differentiated surveillance for sensor networksPublished by Association for Computing Machinery (ACM) ,2003
- Sensor management policies to provide application QoSAd Hoc Networks, 2003
- Connected sensor coverPublished by Association for Computing Machinery (ACM) ,2003
- Distributed Sampling for Dense Sensor Networks: A “Bit-Conservation Principle”Published by Springer Nature ,2003
- A node scheduling scheme for energy conservation in large wireless sensor networksWireless Communications and Mobile Computing, 2003
- Distributed compression in a dense microsensor networkIEEE Signal Processing Magazine, 2002
- Digital halftoning technique using a blue-noise maskJournal of the Optical Society of America A, 1992
- Dithering with blue noiseProceedings of the IEEE, 1988
- Iterative reconstruction of bandlimited images from nonuniformly spaced samplesIEEE Transactions on Circuits and Systems, 1987
- Least squares quantization in PCMIEEE Transactions on Information Theory, 1982