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Self-stabilising target counting in wireless sensor networks using Euler integration

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Pianini_2017_Self_stabilising_target_SASO2017_AAM.pdf (526.0Kb)
Date
12/10/2017
Author
Pianini, Danilo
Dobson, Simon Andrew
Viroli, Mirko
Keywords
Wireless Sensor Networks
Algebraic Topology
Self-stabilising Algorithms
QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
DAS
BDC
R2C
~DC~
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Abstract
Target counting is an established challenge for sensor networks: given a set of sensors that can count (but not identify) targets, how many targets are there? The problem is complicated because of the need to disambiguate duplicate observations of the same target by different sensors. A number of approaches have been proposed in the literature, and in this paper we take an existing technique based on Euler integration and develop a fully-distributed, self-stabilising solution. We derive our algorithm within the field calculus from the centralised presentation of the underlying integration technique, and analyse the precision of the counting through simulation of several network configurations.
Citation
Pianini , D , Dobson , S A & Viroli , M 2017 , Self-stabilising target counting in wireless sensor networks using Euler integration . in 11th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2017) . , 8064025 , International Conference on Self-Adaptive and Self-Organizing Systems , IEEE Computer Society , pp. 11-20 , 11th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2017) , Tucson , United States , 18/09/17 . https://doi.org/10.1109/SASO.2017.10
 
conference
 
Publication
11th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2017)
DOI
https://doi.org/10.1109/SASO.2017.10
ISSN
1949-3673
Type
Conference item
Rights
Copyright © IEEE, 2017. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1109/SASO.2017.10
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/11689

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