NDLI: Self-Organized Distributed Compressive Projection in Large Scale Wireless Sensor Networks

Content Provider	IEEE Xplore Digital Library
Author	Chidean, M.I. Morgado, E. Ramiro, J. Caamano, A.J.
Copyright Year	2013
Description	Author affiliation: Signal Theor. & Commun. Dept., Rey Juan Carlos Univ. Camino del Molino, Fuenlabrada, Spain (Chidean, M.I.; Morgado, E.; Ramiro, J.; Caamano, A.J.)
Abstract	The optimal configuration for a Large Scale Wireless Sensor Networks (LS-WSN) is the one that minimizes the sampling rate, the CPU time and the channel accesses (thus maximizing the network lifetime), with a controlled distortion in the recovered data. Initial deployments of LS-WSN are usually not able to adapt to changing environments and rarely take into account either the spatial or temporal nature of the sensed variables, both techniques that optimize the network operation. In this work we propose the use of Self-Organized Distributed Compressive Projection (SODCP) in order to let the nodes to form clusters in a distributed and data-driven way, exploiting the spatial correlation of the sensed data. We compare the performance of this innovative technique, using actual data from the LUCE LS-WSN, with two different baselines: Centralized Compressive Projection (CCP) and Distributed Compressive Projection (DCP). The former uses no clustering, whereas the latter makes use of an a priori clustering that favors proximity and balances the number of nodes in each cluster. We show that SODCP outperforms DCP (in terms of Signal-to-Noise vs. Compression Rate). We also show that the performance of SODCP converges to that of CCP for relatively high compression rates of 55%.
Starting Page	2000
Ending Page	2004
File Size	774571
Page Count	5
File Format	PDF
ISBN	9781467362351
ISSN	21669570
DOI	10.1109/PIMRC.2013.6666472
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-08
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wireless sensor networks Nickel Clustering algorithms Principal component analysis Encoding Signal to noise ratio Correlation Distributed algorithms Compressive Projection Self-Organization Wireless Sensor Networks Data compression
Content Type	Text
Resource Type	Article

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