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A distributed wavelet compression algorithm for wireless sensor networks using lifting

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2 Author(s)
A. Ciancio ; Signal & Image Process. Inst., Univ. of Southern California, USA ; A. Ortega

We address the problem of compression for wireless sensor networks, where each of the sensors has limited power, and acquires data that should be sent to a remote central node. The final goal is to have a reconstructed version of the sampled field at the central node, with the sensors spending as little energy as possible. We propose a distributed wavelet algorithm, based on the lifting scheme, as a means to decorrelate data at the nodes by exchanging information between neighboring sensors. A key result of our work is that by using a locally adaptive distributed transform it is possible to optimize overall power consumption by operating at the right trade-off point between local processing and transmission costs.

Published in:

Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on  (Volume:4 )

Date of Conference:

17-21 May 2004