A Decentralized Quality Aware Adaptive Sampling Strategy in Wireless Sensor Networks

Alireza Masoum; Nirvana Meratnia; Paul J.M. Havinga

doi:10.1109/UIC-ATC.2012.156

A Decentralized Quality Aware Adaptive Sampling Strategy in Wireless Sensor Networks

Alireza Masoum, Nirvana Meratnia, Paul J.M. Havinga

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

6 Citations (Scopus)

90 Downloads (Pure)

Abstract

Since WSNs suffer from sever resource constraints, in terms of energy, memory and processing, temporal, spatial and spatio-temporal correlation among sensor data can be exploited by adaptive sampling approaches to find out an optimal sampling strategy, which reduces the number of sampling nodes and/or sampling rates while maintaining high data quality. In this paper, a quality aware decentralized adaptive sampling strategy is proposed which benefit from the data correlation for predicting future samples. In this algorithm, sensor nodes adjust their sampling rates, based on environmental conditions and user defined data range. Simulation results show that proposed approach provides 90 percentage event detection accuracy level while consumes lesser energy rather than existing adaptive sampling approach.

Original language	Undefined
Title of host publication	9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012
Place of Publication	USA
Publisher	IEEE Computer Society
Pages	298-305
Number of pages	8
ISBN (Print)	978-1-4673-3084-8
DOIs	https://doi.org/10.1109/UIC-ATC.2012.156
Publication status	Published - Sep 2012
Event	IEEE 9th International Conference on Ubiquitous Intelligence and Computing, UIC 2012 - Fukuoka, Japan Duration: 4 Sep 2012 → 7 Sep 2012 Conference number: 9

Publication series

Name
Publisher	IEEE Computer Society

Conference

Conference	IEEE 9th International Conference on Ubiquitous Intelligence and Computing, UIC 2012
Abbreviated title	UIC
Country	Japan
City	Fukuoka
Period	4/09/12 → 7/09/12

Keywords

EWI-22543
IR-83420
METIS-293201

Cite this

Masoum, A., Meratnia, N., & Havinga, P. J. M. (2012). A Decentralized Quality Aware Adaptive Sampling Strategy in Wireless Sensor Networks. In 9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012 (pp. 298-305). USA: IEEE Computer Society. https://doi.org/10.1109/UIC-ATC.2012.156

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abstract = "Since WSNs suffer from sever resource constraints, in terms of energy, memory and processing, temporal, spatial and spatio-temporal correlation among sensor data can be exploited by adaptive sampling approaches to find out an optimal sampling strategy, which reduces the number of sampling nodes and/or sampling rates while maintaining high data quality. In this paper, a quality aware decentralized adaptive sampling strategy is proposed which benefit from the data correlation for predicting future samples. In this algorithm, sensor nodes adjust their sampling rates, based on environmental conditions and user defined data range. Simulation results show that proposed approach provides 90 percentage event detection accuracy level while consumes lesser energy rather than existing adaptive sampling approach.",

keywords = "EWI-22543, IR-83420, METIS-293201",

author = "Alireza Masoum and Nirvana Meratnia and Havinga, {Paul J.M.}",

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language = "Undefined",

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Masoum, A, Meratnia, N & Havinga, PJM 2012, A Decentralized Quality Aware Adaptive Sampling Strategy in Wireless Sensor Networks. in 9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012. IEEE Computer Society, USA, pp. 298-305, IEEE 9th International Conference on Ubiquitous Intelligence and Computing, UIC 2012, Fukuoka, Japan, 4/09/12. https://doi.org/10.1109/UIC-ATC.2012.156

A Decentralized Quality Aware Adaptive Sampling Strategy in Wireless Sensor Networks. / Masoum, Alireza; Meratnia, Nirvana ; Havinga, Paul J.M.

9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012. USA : IEEE Computer Society, 2012. p. 298-305.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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N2 - Since WSNs suffer from sever resource constraints, in terms of energy, memory and processing, temporal, spatial and spatio-temporal correlation among sensor data can be exploited by adaptive sampling approaches to find out an optimal sampling strategy, which reduces the number of sampling nodes and/or sampling rates while maintaining high data quality. In this paper, a quality aware decentralized adaptive sampling strategy is proposed which benefit from the data correlation for predicting future samples. In this algorithm, sensor nodes adjust their sampling rates, based on environmental conditions and user defined data range. Simulation results show that proposed approach provides 90 percentage event detection accuracy level while consumes lesser energy rather than existing adaptive sampling approach.

AB - Since WSNs suffer from sever resource constraints, in terms of energy, memory and processing, temporal, spatial and spatio-temporal correlation among sensor data can be exploited by adaptive sampling approaches to find out an optimal sampling strategy, which reduces the number of sampling nodes and/or sampling rates while maintaining high data quality. In this paper, a quality aware decentralized adaptive sampling strategy is proposed which benefit from the data correlation for predicting future samples. In this algorithm, sensor nodes adjust their sampling rates, based on environmental conditions and user defined data range. Simulation results show that proposed approach provides 90 percentage event detection accuracy level while consumes lesser energy rather than existing adaptive sampling approach.

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Access to Document

10.1109/UIC-ATC.2012.156

06332012
open