Interval data fusion with preference aggregation in wireless sensor network: energy-accuracy trade-off in presence of outliers; Journal of Physics: Conference Series; Vol. 1065 : International Measurement Confederation (IMEKO 2018)

Détails bibliographiques
Parent link:Journal of Physics: Conference Series
Vol. 1065 : International Measurement Confederation (IMEKO 2018).— 2018.— [202005, 4 р.]
Auteur principal: Khudonogova L. I. Ludmila Igorevna
Collectivité auteur: Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники Отделение автоматизации и робототехники (ОАР)
Autres auteurs: Muravyov (Murav’ev) S. V. Sergey Vasilyevich
Résumé:Title screen
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.
Langue:anglais
Publié: 2018
Sujets:
Accès en ligne:http://earchive.tpu.ru/handle/11683/57371
https://doi.org/10.1088/1742-6596/1065/7/072016
Format: Électronique Chapitre de livre
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=660727

MARC

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330 |a 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. 
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