Evidence map›Paper›PMID 39771615›Full record

ArticleSensors (Basel, Switzerland)2024

Connectivity Recovery Based on Boundary Nodes and Spatial Triangle Fermat Points for Three-Dimensional Wireless Sensor Networks.

Hongsheng Chen, Ke Shi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Hongsheng ChenCollege of Computer Science and Technology, Hubei University of Science and Technology, Xianning 437100, China.
Ke ShiSchool of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.ORCID 0000-0002-4250-6208

Funding

Natural Science Foundation of Hubei Province 2021CFB388The Young Talent Project of Hubei Provincial Department of Education B2021226
6 · The paper itself

Abstract

In recent years, wireless sensor networks have been widely used, especially in three-dimensional environments such as underwater and mountain environments. However, in harsh environments, wireless sensor networks may be damaged and split into many isolated islands. Therefore, restoring network connectivity to transmit data effectively in a timely manner is particularly important. However, the problem of finding the minimum relay nodes is NP-hard, so heuristics methods are preferred. This paper presents a novel connectivity recovery strategy based on boundary nodes and spatial triangle Fermat points for three-dimensional wireless sensor networks. The isolated islands are represented as the boundary nodes, and the connectivity recovery problem is modeled as a graph connectivity problem. Three heuristics algorithms-the variant Kruskal algorithm, the variant Prim algorithm, and the spatial triangle Fermat point algorithm-are proposed to solve this problem. The variant Kruskal algorithm and the variant Prim algorithm connect the isolated islands by constructing the minimum spanning tree to link all the boundary nodes and placing relay nodes along the edges of this tree. We derive an accurate formula to determine the coordinates of spatial triangle Fermat points. Based on this formula, the spatial triangle Fermat point algorithm constructs a Steiner tree to restore network connectivity. Extensive simulation experiments demonstrate that our proposed algorithms perform better than the existing algorithm.

Indexed as

boundary nodesconnectivity recoveryheuristics algorithmsspatial triangle Fermat pointsthree-dimensional wireless sensor networks

Identifiers

PMID39771615
PMCPMC11679557

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.