Principal component analysis-based data reduction model for wireless sensor networks

Wireless sensor networks (WSNs) are widely used in monitoring environmental and physical conditions, such as temperature, vibration, humidity, light and voltage. However, the high dimension of sensed data, especially in multivariate sensor applications, increases the power consumption in transmittin...

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Main Authors: Rassam, Murad Abdo, Zainal, Anazida, Maarof, Mohd. Aizaini
Format: Article
Published: Inderscience Enterprises Ltd 2015
Subjects:
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author Rassam, Murad Abdo
Zainal, Anazida
Maarof, Mohd. Aizaini
author_facet Rassam, Murad Abdo
Zainal, Anazida
Maarof, Mohd. Aizaini
author_sort Rassam, Murad Abdo
collection ePrints
description Wireless sensor networks (WSNs) are widely used in monitoring environmental and physical conditions, such as temperature, vibration, humidity, light and voltage. However, the high dimension of sensed data, especially in multivariate sensor applications, increases the power consumption in transmitting this data to the base station and hence shortens the lifetime of sensors. Therefore, efficient data reduction methods are needed to minimise the power consumption in data transmission. In this paper, an efficient model for multivariate data reduction is proposed based on the principal component analysis (PCA). The performance of the model was evaluated using Intel Berkeley Research Lab (IBRL) dataset. The experimental results show the advantages of the proposed model as it allows 50% reduction rate and 96% approximation accuracy after reduction. A comparison with an existing model shows the superiority of the proposed model in terms of approximation accuracy as the reconstruction error is always smaller for different datasets.
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spelling utm.eprints-550632017-08-01T04:48:45Z http://eprints.utm.my/55063/ Principal component analysis-based data reduction model for wireless sensor networks Rassam, Murad Abdo Zainal, Anazida Maarof, Mohd. Aizaini QA75 Electronic computers. Computer science Wireless sensor networks (WSNs) are widely used in monitoring environmental and physical conditions, such as temperature, vibration, humidity, light and voltage. However, the high dimension of sensed data, especially in multivariate sensor applications, increases the power consumption in transmitting this data to the base station and hence shortens the lifetime of sensors. Therefore, efficient data reduction methods are needed to minimise the power consumption in data transmission. In this paper, an efficient model for multivariate data reduction is proposed based on the principal component analysis (PCA). The performance of the model was evaluated using Intel Berkeley Research Lab (IBRL) dataset. The experimental results show the advantages of the proposed model as it allows 50% reduction rate and 96% approximation accuracy after reduction. A comparison with an existing model shows the superiority of the proposed model in terms of approximation accuracy as the reconstruction error is always smaller for different datasets. Inderscience Enterprises Ltd 2015-01-01 Article PeerReviewed Rassam, Murad Abdo and Zainal, Anazida and Maarof, Mohd. Aizaini (2015) Principal component analysis-based data reduction model for wireless sensor networks. International Journal of Ad Hoc and Ubiquitous Computing, 18 (1-2). pp. 85-101. ISSN 1743-8225 http://dx.doi.org/10.1504/IJAHUC.2015.067756 DOI:10.1504/IJAHUC.2015.067756
spellingShingle QA75 Electronic computers. Computer science
Rassam, Murad Abdo
Zainal, Anazida
Maarof, Mohd. Aizaini
Principal component analysis-based data reduction model for wireless sensor networks
title Principal component analysis-based data reduction model for wireless sensor networks
title_full Principal component analysis-based data reduction model for wireless sensor networks
title_fullStr Principal component analysis-based data reduction model for wireless sensor networks
title_full_unstemmed Principal component analysis-based data reduction model for wireless sensor networks
title_short Principal component analysis-based data reduction model for wireless sensor networks
title_sort principal component analysis based data reduction model for wireless sensor networks
topic QA75 Electronic computers. Computer science
work_keys_str_mv AT rassammuradabdo principalcomponentanalysisbaseddatareductionmodelforwirelesssensornetworks
AT zainalanazida principalcomponentanalysisbaseddatareductionmodelforwirelesssensornetworks
AT maarofmohdaizaini principalcomponentanalysisbaseddatareductionmodelforwirelesssensornetworks