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A layered approach to in situ data management on a wireless sensor network.

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

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A layered approach to in situ data management on a wireless sensor network. / Roadknight, C.; Parrott, L.; Boyd, N. et al.
2004. Paper presented at Proc. ISSNIP : Intelligent Sensors, Sensor Networks and Information Processing.

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

Harvard

Roadknight, C, Parrott, L, Boyd, N & Marshall, IW 2004, 'A layered approach to in situ data management on a wireless sensor network.', Paper presented at Proc. ISSNIP : Intelligent Sensors, Sensor Networks and Information Processing, 14/12/04 - 17/12/04. <http://ieeexplore.ieee.org/servlet/opac?punumber=9710>

APA

Roadknight, C., Parrott, L., Boyd, N., & Marshall, I. W. (2004). A layered approach to in situ data management on a wireless sensor network.. Paper presented at Proc. ISSNIP : Intelligent Sensors, Sensor Networks and Information Processing. http://ieeexplore.ieee.org/servlet/opac?punumber=9710

Vancouver

Roadknight C, Parrott L, Boyd N, Marshall IW. A layered approach to in situ data management on a wireless sensor network.. 2004. Paper presented at Proc. ISSNIP : Intelligent Sensors, Sensor Networks and Information Processing.

Author

Roadknight, C. ; Parrott, L. ; Boyd, N. et al. / A layered approach to in situ data management on a wireless sensor network. Paper presented at Proc. ISSNIP : Intelligent Sensors, Sensor Networks and Information Processing.5 p.

Bibtex

@conference{1bef0a68b2de4b088b6933b2e972f33a,
title = "A layered approach to in situ data management on a wireless sensor network.",
abstract = "A multi-layered algorithm is proposed that provides a scalable and adaptive method for handling data on a wireless sensor network. Statistical tests, local feedback and global genetic style material exchange ensure limited resources, such as battery and bandwidth, are used efficiently by manipulating data at the source and important features in the time series are not lost when compression needs to be made. The approach leads to a more 'hands off' implementation which is demonstrated by a real world oceanographic deployment of the system.",
keywords = "bandwidth resources battery resources data compression global genetic style material exchange in situ data management local feedback multi-layered algorithm oceanographic deployment statistical tests time series wireless sensor network",
author = "C. Roadknight and L. Parrott and N. Boyd and Marshall, {I. W.}",
note = "{\textcopyright}2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.{"} {"}This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.; Proc. ISSNIP : Intelligent Sensors, Sensor Networks and Information Processing ; Conference date: 14-12-2004 Through 17-12-2004",
year = "2004",
language = "English",

}

RIS

TY - CONF

T1 - A layered approach to in situ data management on a wireless sensor network.

AU - Roadknight, C.

AU - Parrott, L.

AU - Boyd, N.

AU - Marshall, I. W.

N1 - ©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE." "This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

PY - 2004

Y1 - 2004

N2 - A multi-layered algorithm is proposed that provides a scalable and adaptive method for handling data on a wireless sensor network. Statistical tests, local feedback and global genetic style material exchange ensure limited resources, such as battery and bandwidth, are used efficiently by manipulating data at the source and important features in the time series are not lost when compression needs to be made. The approach leads to a more 'hands off' implementation which is demonstrated by a real world oceanographic deployment of the system.

AB - A multi-layered algorithm is proposed that provides a scalable and adaptive method for handling data on a wireless sensor network. Statistical tests, local feedback and global genetic style material exchange ensure limited resources, such as battery and bandwidth, are used efficiently by manipulating data at the source and important features in the time series are not lost when compression needs to be made. The approach leads to a more 'hands off' implementation which is demonstrated by a real world oceanographic deployment of the system.

KW - bandwidth resources battery resources data compression global genetic style material exchange in situ data management local feedback multi-layered algorithm oceanographic deployment statistical tests time series wireless sensor network

M3 - Conference paper

T2 - Proc. ISSNIP : Intelligent Sensors, Sensor Networks and Information Processing

Y2 - 14 December 2004 through 17 December 2004

ER -