NDLI: Distributed data aggregation in sensor networks by regression based compression

Content Provider	IEEE Xplore Digital Library
Author	Banerjee, T. Chowdhury, K. Agrawal, D.P.
Copyright Year	2005
Description	Author affiliation: OBR Center for Distributed & Mobile Comput., Cincinnati Univ., OH (Banerjee, T.; Chowdhury, K.; Agrawal, D.P.)
Abstract	In this paper we propose a method for data compression and its subsequent regeneration using a polynomial regression technique. We approximate data received over the considered area by fitting it to a function and communicate this by passing only the coefficients that describe the function. In this paper, we extend our previous algorithm TREG to consider non-complete aggregation trees. The proposed algorithm DUMMYREG is run at each parent node and uses information present in the existing child to construct a complete binary tree. In addition to obtaining values in regions devoid of sensor nodes and reducing communication overhead, this new approach further reduces the error when the readings are regenerated at the sink. Results reveal that for a network density of 0.0025 and a complete binary tree of depth 4, the absolute error is 6%. For a non-complete binary tree, TREG returns an error of 18% while this is reduced to 12% when DUMMYREG is used
Starting Page	8
Ending Page	290
File Size	488736
Page Count	283
File Format	PDF
ISBN	0780394658
DOI	10.1109/MAHSS.2005.1542811
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-11-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent networks Wireless sensor networks Data compression Binary trees Sensor phenomena and characterization Polynomials Robustness Distributed computing Regression tree analysis Mobile computing
Content Type	Text
Resource Type	Article

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