Energy efficient sampling for event detection in wireless sensor networks

Authors:
Zainul Charbiwala;Younghun Kim;Sadaf Zahedi;Jonathan Friedman;Mani B. Srivastava
Affiliations:
University of California, Los Angeles, Los Angeles, CA, USA;University of California, Los Angeles, Los Angeles, CA, USA;University of California, Los Angeles, Los Angeles, CA, USA;University of California, Los Angeles, Los Angeles, CA, USA;University of California, Los Angeles, Los Angeles, CA, USA
Venue:
Proceedings of the 14th ACM/IEEE international symposium on Low power electronics and design
Year:
2009

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Abstract

Compressive Sensing (CS) is a recently developed mechanism that allows signal acquisition and compression to be performed in one inexpensive step so that the sampling process itself produces a compressed version of the signal. This significantly improves systemic energy efficiency because the average sampling rate can be considerably reduced and explicit compression eliminated. In this paper, we introduce a modification to the canonical CS recovery technique that enables even higher gains for event detection applications. We show a practical implementation of this compressive detection with energy constrained wireless sensor nodes and quantify the gains accrued through simulation and experimentation.