Research Repository

Agent Centric Sensor Network Association using Similarity Measures

Colley, MJ and Stacey, RP (2008) 'Agent Centric Sensor Network Association using Similarity Measures.' In: UNSPECIFIED, (ed.) Pervasive Computing and Applications, 2008. ICPCA 2008. Third International Conference. Institute of Electrical and Electronics Engineers (IEEE), 128 - 133. ISBN 9781424420209

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Abstract

Inside the grouping process of sensor networks each node must decide what local group it is going to be a part of for data aggregation and dissemination. We look at how to form the most likely groups using agent centric methods based on the similarity to other nodes in the network and evaluate methods based on clustering, thresholding and fuzzy logic. The methods use simple scores that represent the similarity to local nodes and are optimised using a genetic algorithm in simulation. Using these methods we achieve an accuracy of around 80% in simulation of a large number of nodes using data obtained from real world data-logging. These results are validated using real world experimentation and we show that fuzzy thresholding outperforms the other methods

Item Type: Book Section
Uncontrolled Keywords: Event Matching; Intelligent Environments; Logical Grouping; Sensor Networks
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Users 161 not found.
Date Deposited: 02 Aug 2012 09:08
Last Modified: 17 Aug 2017 18:09
URI: http://repository.essex.ac.uk/id/eprint/3416

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