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Yuanxiao Ou

dblp:170/2376 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Wireless sensing and localization · 67% Internet of things and sensor networks · 33%
Theoretical computer science
1 paper
Graph algorithms and graph theory · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wireless sensing and localization › sensor network localization
graph rigidity
0.312017
Localizability Judgment in UWSNs Based on Skeleton and Rigidity Theory · IEEE Trans. Mob. Comput. 2017
Wireless sensing and localization
sensor network localization
0.312017
Localizability Judgment in UWSNs Based on Skeleton and Rigidity Theory · IEEE Trans. Mob. Comput. 2017
Internet of things and sensor networks
underwater sensor networks
0.312017
Localizability Judgment in UWSNs Based on Skeleton and Rigidity Theory · IEEE Trans. Mob. Comput. 2017
Graph algorithms and graph theory › graph theory › graph realization
graph rigidity
0.112017
Localizability Judgment in UWSNs Based on Skeleton and Rigidity Theory · IEEE Trans. Mob. Comput. 2017

Methods — techniques the papers use, named apart from their topics

rigidity theory · 0.6analytic hierarchy process · 0.6
YearPublicationVenuePosition
2017 Localizability Judgment in UWSNs Based on Skeleton and Rigidity Theory
abstract
Underwater sensor networks (UWSNs) have been investigated in a variety of applications such as sea resources reconnaissance, pollution monitoring and tactical monitoring. In 3D underwater environments, it is a key topic to judge the localizability of sensor nodes given known locations of a small set of anchor nodes. In this paper, a novel localizability judgment method for UWSNs is proposed based on rigidity theory. A UWSN is modelled as an undirected graph based on acoustic connectivity. The graph is then reduced to a subgraph with global rigidity, called skeleton, from which the set of localizable sensors can determined. Furthermore, the Analytic Hierarchy Process (AHP) is used to evaluate the localization confidence of localizable sensors. Extensive simulations demonstrate that the proposed localizability judgment method can achieve low false negative rate and high efficiency networks of different sensor numbers and sensor densities. It is also shown to perform well in dynamic networks with relatively low waterflow speed.
Na Xia, Yuanxiao Ou, Shiliang Wang, Rong Zheng 0001, Huazheng Du, Chaonong Xu
IEEE Trans. Mob. Comput.2