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Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks

With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be dete...

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Autores principales: Zhou, Zhangbing, Xing, Riliang, Duan, Yucong, Zhu, Yueqin, Xiang, Jianming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721795/
https://www.ncbi.nlm.nih.gov/pubmed/26694394
http://dx.doi.org/10.3390/s151229875
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author Zhou, Zhangbing
Xing, Riliang
Duan, Yucong
Zhu, Yueqin
Xiang, Jianming
author_facet Zhou, Zhangbing
Xing, Riliang
Duan, Yucong
Zhu, Yueqin
Xiang, Jianming
author_sort Zhou, Zhangbing
collection PubMed
description With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sources is developed in this article. Specifically, the occurrence of possible events corresponds to a set of neighboring sensor nodes whose sensory data may deviate from a normal sensing range in a collective fashion. An appropriate sensor node is selected as the relay node for gathering and routing sensory data to sink node(s). When sensory data are collected at sink node(s), the event coverage is detected and represented as a weighted graph, where the vertices in this graph correspond to sensor nodes and the weight specified upon the edges reflects the extent of sensory data deviating from a normal sensing range. Event sources are determined, which correspond to the barycenters in this graph. The results of the experiments show that our technique is more energy efficient, especially when the network topology is relatively steady.
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spelling pubmed-47217952016-01-26 Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks Zhou, Zhangbing Xing, Riliang Duan, Yucong Zhu, Yueqin Xiang, Jianming Sensors (Basel) Article With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sources is developed in this article. Specifically, the occurrence of possible events corresponds to a set of neighboring sensor nodes whose sensory data may deviate from a normal sensing range in a collective fashion. An appropriate sensor node is selected as the relay node for gathering and routing sensory data to sink node(s). When sensory data are collected at sink node(s), the event coverage is detected and represented as a weighted graph, where the vertices in this graph correspond to sensor nodes and the weight specified upon the edges reflects the extent of sensory data deviating from a normal sensing range. Event sources are determined, which correspond to the barycenters in this graph. The results of the experiments show that our technique is more energy efficient, especially when the network topology is relatively steady. MDPI 2015-12-15 /pmc/articles/PMC4721795/ /pubmed/26694394 http://dx.doi.org/10.3390/s151229875 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhou, Zhangbing
Xing, Riliang
Duan, Yucong
Zhu, Yueqin
Xiang, Jianming
Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks
title Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks
title_full Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks
title_fullStr Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks
title_full_unstemmed Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks
title_short Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks
title_sort event coverage detection and event source determination in underwater wireless sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721795/
https://www.ncbi.nlm.nih.gov/pubmed/26694394
http://dx.doi.org/10.3390/s151229875
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