Comparison of different data prediction methods for wireless sensor networks

Date Issued
2013-04
Author(s)
Risteska Stojkoska, Biljana
Mahoski, Kliment
Abstract
Different data reduction strategies have been developed in
order to reduce the energy consumption in wireless sensor
networks (WSN). Most of them reduce the amount of sent data
by predicting the measured values both at the source and the
sink, requiring transmission only if a certain reading differs by
a given margin from the predicted values. The subject of this
paper is comparison of a few different techniques for
prediction of time series data in WSN. While these strategies
often provide great reduction in power consumption, they don’t
need a priori knowledge of the explored domain in order to
correctly model the expected values.
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