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Goldoni, E, Savazzi, P and Gamba, P (2012)

A novel source coding technique for wireless sensor networks based on Benford's law

2012 IEEE Workshop on Environmental Energy and Structural Monitoring Systems (EESMS), 26-28 Sept. 2012, pp 32-34 .

ISSN/ISBN: 978-1-4673-2739-8 DOI: Not available at this time.

Abstract: Since its discovery in 1881, Benford's law has been verified in several application fields related to economics, physics and even in number theory. In particular, a random dataset obtained from physical measurements seems to be the best empirical example of its validity. Following this reasoning, we present a novel and fast source coding algorithm for wireless sensor measurements. In more details, the Benford's probability density distribution is exploited for Huffmann coding of measured values, considering the Benford probability density of the first digit. This results may be fast obtained assuming the Benford's law validity, without directly computing the a priori probabilities of the measured digits. Performance evaluation is provided by system simulations, comparing the obtained results with the computed a posteriori source entropy.

@INPROCEEDINGS{6348393, author={Goldoni, E. and Savazzi, P. and Gamba, P.}, booktitle={Environmental Energy and Structural Monitoring Systems (EESMS), 2012 IEEE Workshop on}, title={A novel source coding technique for wireless sensor networks based on Benford's law}, year={2012}, pages={32-34}, keywords={entropy codes;source coding;statistical distributions;wireless sensor networks;Benford law;Benford probability density distribution;a priori probability;fast source coding algorithm;number theory;posteriori source entropy code;random dataset;source coding technique;system simulations;wireless sensor measurements;wireless sensor networks;Atmospheric measurements;Particle measurements;Source coding;Wireless communication;Wireless sensor networks}, doi={10.1109/EESMS.2012.6348393},}

Reference Type: Conference Paper

Subject Area(s): Computer Science