Home > Research > Publications & Outputs > A Biologically-Inspired Clustering Algorithm De...
View graph of relations

A Biologically-Inspired Clustering Algorithm Dependent on Spatial Data in Sensor Networks.

Research output: Contribution to conference - Without ISBN/ISSN Conference paperpeer-review

Published

Standard

A Biologically-Inspired Clustering Algorithm Dependent on Spatial Data in Sensor Networks. / Wokoma, Ibiso; Ling Shum, Lam; Sacks, Lionel; Marshall, Ian.

2005. Paper presented at Proceedings of the Second European Workshop on Wireless Sensor Networks, 2005..

Research output: Contribution to conference - Without ISBN/ISSN Conference paperpeer-review

Harvard

Wokoma, I, Ling Shum, L, Sacks, L & Marshall, I 2005, 'A Biologically-Inspired Clustering Algorithm Dependent on Spatial Data in Sensor Networks.', Paper presented at Proceedings of the Second European Workshop on Wireless Sensor Networks, 2005., 31/01/05 - 2/02/05. <http://ieeexplore.ieee.org/xpl/RecentCon.jsp?punumber=9875>

APA

Wokoma, I., Ling Shum, L., Sacks, L., & Marshall, I. (2005). A Biologically-Inspired Clustering Algorithm Dependent on Spatial Data in Sensor Networks.. Paper presented at Proceedings of the Second European Workshop on Wireless Sensor Networks, 2005.. http://ieeexplore.ieee.org/xpl/RecentCon.jsp?punumber=9875

Vancouver

Wokoma I, Ling Shum L, Sacks L, Marshall I. A Biologically-Inspired Clustering Algorithm Dependent on Spatial Data in Sensor Networks.. 2005. Paper presented at Proceedings of the Second European Workshop on Wireless Sensor Networks, 2005..

Author

Wokoma, Ibiso ; Ling Shum, Lam ; Sacks, Lionel ; Marshall, Ian. / A Biologically-Inspired Clustering Algorithm Dependent on Spatial Data in Sensor Networks. Paper presented at Proceedings of the Second European Workshop on Wireless Sensor Networks, 2005..11 p.

Bibtex

@conference{0ec6c84f07214b38952dadaa57c7484c,
title = "A Biologically-Inspired Clustering Algorithm Dependent on Spatial Data in Sensor Networks.",
abstract = "Sensor networks in environmental monitoring applications aim to provide scientists with a useful spatio-temporal representation of the observed phenomena. This helps to deepen their understanding of the environmental signals that cover large geographic areas. In this paper, the spatial aspect of this data handling requirement is met by creating clusters in a sensor network based on the rate of change of an oceanographic signal with respect to space. Inspiration was drawn from quorum sensing, a biological process that is carried out within communities of bacterial cells. The paper demonstrates the control the user has over the sensitivity of the algorithm to the data variation and the energy consumption of the nodes while they run the algorithm.",
keywords = "algorithm bacterial cell biological process data handling requirement energy consumption environmental monitoring application geographic area oceanographic signal quorum sensing scientists sensitivity sensor network sensor network cluster spatio-temporal representation",
author = "Ibiso Wokoma and {Ling Shum}, Lam and Lionel Sacks and Ian Marshall",
note = "{\textcopyright}2005 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.; Proceedings of the Second European Workshop on Wireless Sensor Networks, 2005. ; Conference date: 31-01-2005 Through 02-02-2005",
year = "2005",
language = "English",

}

RIS

TY - CONF

T1 - A Biologically-Inspired Clustering Algorithm Dependent on Spatial Data in Sensor Networks.

AU - Wokoma, Ibiso

AU - Ling Shum, Lam

AU - Sacks, Lionel

AU - Marshall, Ian

N1 - ©2005 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 - 2005

Y1 - 2005

N2 - Sensor networks in environmental monitoring applications aim to provide scientists with a useful spatio-temporal representation of the observed phenomena. This helps to deepen their understanding of the environmental signals that cover large geographic areas. In this paper, the spatial aspect of this data handling requirement is met by creating clusters in a sensor network based on the rate of change of an oceanographic signal with respect to space. Inspiration was drawn from quorum sensing, a biological process that is carried out within communities of bacterial cells. The paper demonstrates the control the user has over the sensitivity of the algorithm to the data variation and the energy consumption of the nodes while they run the algorithm.

AB - Sensor networks in environmental monitoring applications aim to provide scientists with a useful spatio-temporal representation of the observed phenomena. This helps to deepen their understanding of the environmental signals that cover large geographic areas. In this paper, the spatial aspect of this data handling requirement is met by creating clusters in a sensor network based on the rate of change of an oceanographic signal with respect to space. Inspiration was drawn from quorum sensing, a biological process that is carried out within communities of bacterial cells. The paper demonstrates the control the user has over the sensitivity of the algorithm to the data variation and the energy consumption of the nodes while they run the algorithm.

KW - algorithm bacterial cell biological process data handling requirement energy consumption environmental monitoring application geographic area oceanographic signal quorum sensing scientists sensitivity sensor network sensor network cluster spatio-temporal

M3 - Conference paper

T2 - Proceedings of the Second European Workshop on Wireless Sensor Networks, 2005.

Y2 - 31 January 2005 through 2 February 2005

ER -