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Self Organisation in Ad-Hoc Sensor Networks: An Empirical Study

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

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Self Organisation in Ad-Hoc Sensor Networks: An Empirical Study. / Catterall, Elaine; Van Laerhoven, Kristof; Strohbach, Martin.
2002. Paper presented at ICAL 2003: Proceedings of the eighth international conference on Artificial life.

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

Harvard

Catterall, E, Van Laerhoven, K & Strohbach, M 2002, 'Self Organisation in Ad-Hoc Sensor Networks: An Empirical Study', Paper presented at ICAL 2003: Proceedings of the eighth international conference on Artificial life, 1/01/00.

APA

Catterall, E., Van Laerhoven, K., & Strohbach, M. (2002). Self Organisation in Ad-Hoc Sensor Networks: An Empirical Study. Paper presented at ICAL 2003: Proceedings of the eighth international conference on Artificial life.

Vancouver

Catterall E, Van Laerhoven K, Strohbach M. Self Organisation in Ad-Hoc Sensor Networks: An Empirical Study. 2002. Paper presented at ICAL 2003: Proceedings of the eighth international conference on Artificial life.

Author

Catterall, Elaine ; Van Laerhoven, Kristof ; Strohbach, Martin. / Self Organisation in Ad-Hoc Sensor Networks: An Empirical Study. Paper presented at ICAL 2003: Proceedings of the eighth international conference on Artificial life.

Bibtex

@conference{3b17a94812ce4a7fa0362a2a490f6e85,
title = "Self Organisation in Ad-Hoc Sensor Networks: An Empirical Study",
abstract = "Research in classifying and recognizing complex concepts has been directing its focus increasingly on distributed sensing using a large amount of sensors. The colossal amount of sensor data often obstructs traditional algorithms in centralized approaches, where all sensor data is directed to one central location to be processed. Spreading the processing of sensor data over the network seems to be a promising option, but distributed algorithms are harder to inspect and evaluate. Using self-sufficient sensor boards with short-range wireless communication capabilities, we are exploring approaches to achieve an emerging distributed perception of the sensed environment in real-time through clustering. Experiments in both simulation and real-world platforms indicate that this is a valid methodology, being especially promising for computation on many units with limited resources.",
keywords = "cs_eprint_id, 673 cs_uid, 1",
author = "Elaine Catterall and {Van Laerhoven}, Kristof and Martin Strohbach",
year = "2002",
month = dec,
language = "English",
note = "ICAL 2003: Proceedings of the eighth international conference on Artificial life ; Conference date: 01-01-1900",

}

RIS

TY - CONF

T1 - Self Organisation in Ad-Hoc Sensor Networks: An Empirical Study

AU - Catterall, Elaine

AU - Van Laerhoven, Kristof

AU - Strohbach, Martin

PY - 2002/12

Y1 - 2002/12

N2 - Research in classifying and recognizing complex concepts has been directing its focus increasingly on distributed sensing using a large amount of sensors. The colossal amount of sensor data often obstructs traditional algorithms in centralized approaches, where all sensor data is directed to one central location to be processed. Spreading the processing of sensor data over the network seems to be a promising option, but distributed algorithms are harder to inspect and evaluate. Using self-sufficient sensor boards with short-range wireless communication capabilities, we are exploring approaches to achieve an emerging distributed perception of the sensed environment in real-time through clustering. Experiments in both simulation and real-world platforms indicate that this is a valid methodology, being especially promising for computation on many units with limited resources.

AB - Research in classifying and recognizing complex concepts has been directing its focus increasingly on distributed sensing using a large amount of sensors. The colossal amount of sensor data often obstructs traditional algorithms in centralized approaches, where all sensor data is directed to one central location to be processed. Spreading the processing of sensor data over the network seems to be a promising option, but distributed algorithms are harder to inspect and evaluate. Using self-sufficient sensor boards with short-range wireless communication capabilities, we are exploring approaches to achieve an emerging distributed perception of the sensed environment in real-time through clustering. Experiments in both simulation and real-world platforms indicate that this is a valid methodology, being especially promising for computation on many units with limited resources.

KW - cs_eprint_id

KW - 673 cs_uid

KW - 1

M3 - Conference paper

T2 - ICAL 2003: Proceedings of the eighth international conference on Artificial life

Y2 - 1 January 1900

ER -