On localized prediction for power efficient object tracking in sensor networks

Yingqi Xu; Wang Chien Lee

doi:10.1109/ICDCSW.2003.1203591

On localized prediction for power efficient object tracking in sensor networks

Yingqi Xu, Wang Chien Lee

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

107 Scopus citations

Abstract

Energy is one of the most critical constraints for sensor network applications. In this paper, we exploit the localized prediction paradigm for power-efficient object tracking sensor network. Localized prediction consists of a localized network architecture and a prediction mechanism called dual prediction, which achieve power savings by allowing most of the sensor nodes stay in sleep mode and by reducing the amount of long-range transmissions. Performance evaluation, based on mathematical analysis, shows that localized prediction can significantly reduce the power consumption in object tracking sensor networks.

Original language	English (US)
Title of host publication	Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	434-439
Number of pages	6
ISBN (Electronic)	0769519210, 9780769519210
DOIs	https://doi.org/10.1109/ICDCSW.2003.1203591
State	Published - 2003
Event	23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003 - Providence, United States Duration: May 19 2003 → May 22 2003

Publication series

Name	Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003

Other

Other	23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003
Country/Territory	United States
City	Providence
Period	5/19/03 → 5/22/03

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Hardware and Architecture
Signal Processing

Access to Document

10.1109/ICDCSW.2003.1203591

Cite this

Xu, Y., & Lee, W. C. (2003). On localized prediction for power efficient object tracking in sensor networks. In Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003 (pp. 434-439). [1203591] (Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDCSW.2003.1203591

Xu, Yingqi ; Lee, Wang Chien. / On localized prediction for power efficient object tracking in sensor networks. Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003. Institute of Electrical and Electronics Engineers Inc., 2003. pp. 434-439 (Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003).

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title = "On localized prediction for power efficient object tracking in sensor networks",

abstract = "Energy is one of the most critical constraints for sensor network applications. In this paper, we exploit the localized prediction paradigm for power-efficient object tracking sensor network. Localized prediction consists of a localized network architecture and a prediction mechanism called dual prediction, which achieve power savings by allowing most of the sensor nodes stay in sleep mode and by reducing the amount of long-range transmissions. Performance evaluation, based on mathematical analysis, shows that localized prediction can significantly reduce the power consumption in object tracking sensor networks.",

author = "Yingqi Xu and Lee, {Wang Chien}",

note = "Publisher Copyright: {\textcopyright} 2002 IEEE.; 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003 ; Conference date: 19-05-2003 Through 22-05-2003",

year = "2003",

doi = "10.1109/ICDCSW.2003.1203591",

language = "English (US)",

series = "Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003",

address = "United States",

}

Xu, Y & Lee, WC 2003, On localized prediction for power efficient object tracking in sensor networks. in Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003., 1203591, Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003, Institute of Electrical and Electronics Engineers Inc., pp. 434-439, 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003, Providence, United States, 5/19/03. https://doi.org/10.1109/ICDCSW.2003.1203591

On localized prediction for power efficient object tracking in sensor networks. / Xu, Yingqi; Lee, Wang Chien.

Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003. Institute of Electrical and Electronics Engineers Inc., 2003. p. 434-439 1203591 (Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - On localized prediction for power efficient object tracking in sensor networks

AU - Xu, Yingqi

AU - Lee, Wang Chien

PY - 2003

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N2 - Energy is one of the most critical constraints for sensor network applications. In this paper, we exploit the localized prediction paradigm for power-efficient object tracking sensor network. Localized prediction consists of a localized network architecture and a prediction mechanism called dual prediction, which achieve power savings by allowing most of the sensor nodes stay in sleep mode and by reducing the amount of long-range transmissions. Performance evaluation, based on mathematical analysis, shows that localized prediction can significantly reduce the power consumption in object tracking sensor networks.

AB - Energy is one of the most critical constraints for sensor network applications. In this paper, we exploit the localized prediction paradigm for power-efficient object tracking sensor network. Localized prediction consists of a localized network architecture and a prediction mechanism called dual prediction, which achieve power savings by allowing most of the sensor nodes stay in sleep mode and by reducing the amount of long-range transmissions. Performance evaluation, based on mathematical analysis, shows that localized prediction can significantly reduce the power consumption in object tracking sensor networks.

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M3 - Conference contribution

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BT - Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003

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ER -

Xu Y, Lee WC. On localized prediction for power efficient object tracking in sensor networks. In Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003. Institute of Electrical and Electronics Engineers Inc. 2003. p. 434-439. 1203591. (Proceedings - 23rd International Conference on Distributed Computing Systems Workshops, ICDCSW 2003). doi: 10.1109/ICDCSW.2003.1203591

On localized prediction for power efficient object tracking in sensor networks

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