Energy-accuracy aware active node selection in wireless sensor networks

Bibliographische Detailangaben
Parent link:Control and Communications (SIBCON): Proceedings of the XII International Siberian Conference, Moscow, May 12-14, 2016. [5 p.].— , 2016
1. Verfasser: Khudonogova L. I. Ludmila Igorevna
Körperschaft: Национальный исследовательский Томский политехнический университет (ТПУ) Институт кибернетики (ИК) Кафедра информатики и проектирования систем (ИПС)
Weitere Verfasser: Muravyov (Murav’ev) S. V. Sergey Vasilyevich
Zusammenfassung:Title screen
One of the main issues in wireless sensor networks (WSNs) is energy conservation due to limited power of sensor node battery. To save energy, WSNs operate in duty-cycling work mode, when the sensor nodes alternate between active and dormant states. In this paper, we propose an active node set selection algorithm (ANSS), based on preference aggregation. The aim of the algorithm is to reduce the number of active sensor nodes, thus decreasing energy consumption while keeping required measurement accuracy level. Nodes, included in the active node set, are selected on the base of such parameters as energy consumption, distance to a cluster head, and multisensor general accuracy.
Sprache:Englisch
Veröffentlicht: 2016
Schlagworte:
Online-Zugang:https://doi.org/10.1109/SIBCON.2016.7491835
Format: Elektronisch Buchkapitel
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=653729

MARC

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330 |a One of the main issues in wireless sensor networks (WSNs) is energy conservation due to limited power of sensor node battery. To save energy, WSNs operate in duty-cycling work mode, when the sensor nodes alternate between active and dormant states. In this paper, we propose an active node set selection algorithm (ANSS), based on preference aggregation. The aim of the algorithm is to reduce the number of active sensor nodes, thus decreasing energy consumption while keeping required measurement accuracy level. Nodes, included in the active node set, are selected on the base of such parameters as energy consumption, distance to a cluster head, and multisensor general accuracy. 
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