Interval data fusion with preference aggregation in wireless sensor network

Energy-accuracy trade-off in presence of outliers

Research output: Contribution to journalConference article

Abstract

For balancing measurement accuracy and energy consumption in a wireless sensor network in presence of outliers it is proposed sensor accuracy enhancement algorithm SensAcc and active node selection algorithm ActiveNode based on the interval data fusion method IF&PA. The results of numerical experimental investigation of the developed algorithms are presented. It is shown that the SensAcc provides the reduction of the uncertainty of measurement result at least tenfold comparing with the uncertainty of multisensor readings under possible existence of failed nodes. Simulation results have shown the ActiveNode allows to reduce the cluster nodes energy consumption approximately threefold.

Original languageEnglish
Article number072016
JournalJournal of Physics: Conference Series
Volume1065
Issue number7
DOIs
Publication statusPublished - 13 Nov 2018
Event22nd World Congress of the International Measurement Confederation, IMEKO 2018 - Belfast, United Kingdom
Duration: 3 Sep 20186 Sep 2018

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multisensor fusion
energy consumption
intervals
sensors
energy
augmentation
simulation

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

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abstract = "For balancing measurement accuracy and energy consumption in a wireless sensor network in presence of outliers it is proposed sensor accuracy enhancement algorithm SensAcc and active node selection algorithm ActiveNode based on the interval data fusion method IF&PA. The results of numerical experimental investigation of the developed algorithms are presented. It is shown that the SensAcc provides the reduction of the uncertainty of measurement result at least tenfold comparing with the uncertainty of multisensor readings under possible existence of failed nodes. Simulation results have shown the ActiveNode allows to reduce the cluster nodes energy consumption approximately threefold.",
author = "Khudonogova, {L. I.} and Muravyov, {S. V.}",
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