Distributed Principal Component Analysis for Wireless Sensor Networks
The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like compression, event detection, and event recognition. This technique is based on a linear transform where the sensor measurements a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2008-08-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/8/8/4821/ |
| _version_ | 1828393968400859136 |
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| author | Gianluca Bontempi Sylvain Raybaud Yann-Aël Le Borgne |
| author_facet | Gianluca Bontempi Sylvain Raybaud Yann-Aël Le Borgne |
| author_sort | Gianluca Bontempi |
| collection | DOAJ |
| description | The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like compression, event detection, and event recognition. This technique is based on a linear transform where the sensor measurements are projected on a set of principal components. When sensor measurements are correlated, a small set of principal components can explain most of the measurements variability. This allows to significantly decrease the amount of radio communication and of energy consumption. In this paper, we show that the power iteration method can be distributed in a sensor network in order to compute an approximation of the principal components. The proposed implementation relies on an aggregation service, which has recently been shown to provide a suitable framework for distributing the computation of a linear transform within a sensor network. We also extend this previous work by providing a detailed analysis of the computational, memory, and communication costs involved. A compression experiment involving real data validates the algorithm and illustrates the tradeoffs between accuracy and communication costs. |
| first_indexed | 2024-12-10T07:47:48Z |
| format | Article |
| id | doaj.art-520d3e7db00d42c680099418411c0035 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-12-10T07:47:48Z |
| publishDate | 2008-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-520d3e7db00d42c680099418411c00352022-12-22T01:57:08ZengMDPI AGSensors1424-82202008-08-018848214850Distributed Principal Component Analysis for Wireless Sensor NetworksGianluca BontempiSylvain RaybaudYann-Aël Le BorgneThe Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like compression, event detection, and event recognition. This technique is based on a linear transform where the sensor measurements are projected on a set of principal components. When sensor measurements are correlated, a small set of principal components can explain most of the measurements variability. This allows to significantly decrease the amount of radio communication and of energy consumption. In this paper, we show that the power iteration method can be distributed in a sensor network in order to compute an approximation of the principal components. The proposed implementation relies on an aggregation service, which has recently been shown to provide a suitable framework for distributing the computation of a linear transform within a sensor network. We also extend this previous work by providing a detailed analysis of the computational, memory, and communication costs involved. A compression experiment involving real data validates the algorithm and illustrates the tradeoffs between accuracy and communication costs.http://www.mdpi.com/1424-8220/8/8/4821/Wireless sensor networksdistributed principal component analysisin-network aggregationpower iteration method. |
| spellingShingle | Gianluca Bontempi Sylvain Raybaud Yann-Aël Le Borgne Distributed Principal Component Analysis for Wireless Sensor Networks Sensors Wireless sensor networks distributed principal component analysis in-network aggregation power iteration method. |
| title | Distributed Principal Component Analysis for Wireless Sensor Networks |
| title_full | Distributed Principal Component Analysis for Wireless Sensor Networks |
| title_fullStr | Distributed Principal Component Analysis for Wireless Sensor Networks |
| title_full_unstemmed | Distributed Principal Component Analysis for Wireless Sensor Networks |
| title_short | Distributed Principal Component Analysis for Wireless Sensor Networks |
| title_sort | distributed principal component analysis for wireless sensor networks |
| topic | Wireless sensor networks distributed principal component analysis in-network aggregation power iteration method. |
| url | http://www.mdpi.com/1424-8220/8/8/4821/ |
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