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Authors: Shu-Yuan Wu 1 ; Theodore Brown 1 ; 2 and Hsien-Tseng Wang 3

Affiliations: 1 Graduate Center, City University of New York, New York, U.S.A. ; 2 Queens College, City University of New York, New York, U.S.A. ; 3 Lehman College, City University of New York, New York, U.S.A.

Keyword(s): Reaction-Diffusion, Activator-inhibitor, Wireless Sensor Networks.

Abstract: Alan Turing introduced a novel Reaction-Diffusion (RD) model in 1952 to explain biological pattern formation found in animals. Since then, studies based on the RD model have long proved the feasibility of adapting it to spatial patern formation in distributed systems, especially in networking systems. In the past two decades, RD mechanism started being applied to Wireless Sensor Networks, and the possiblity of expanding to new applications is promising. In this paper, we first review the original RD model and further show its variants, known as activator-inhibitor models. Several research efforts on applying them to model tasks in wireless sensor networks will be presented and summarized.

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Paper citation in several formats:
Wu, S.; Brown, T. and Wang, H. (2022). Reaction-Diffusion Inspired Sensor Networking: From Theory to Application. In Proceedings of the 11th International Conference on Sensor Networks - SENSORNETS; ISBN 978-989-758-551-7; ISSN 2184-4380, SciTePress, pages 231-238. DOI: 10.5220/0010993300003118

@conference{sensornets22,
author={Shu{-}Yuan Wu. and Theodore Brown. and Hsien{-}Tseng Wang.},
title={Reaction-Diffusion Inspired Sensor Networking: From Theory to Application},
booktitle={Proceedings of the 11th International Conference on Sensor Networks - SENSORNETS},
year={2022},
pages={231-238},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010993300003118},
isbn={978-989-758-551-7},
issn={2184-4380},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Sensor Networks - SENSORNETS
TI - Reaction-Diffusion Inspired Sensor Networking: From Theory to Application
SN - 978-989-758-551-7
IS - 2184-4380
AU - Wu, S.
AU - Brown, T.
AU - Wang, H.
PY - 2022
SP - 231
EP - 238
DO - 10.5220/0010993300003118
PB - SciTePress

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