Evidence map›Paper›PMID 32796557›Full record

ArticleSensors (Basel, Switzerland)2020

Node Deployment of Marine Monitoring Networks: A Multiobjective Optimization Scheme.

Jian-Li Duan, Bin Lin, Lin X Cai, Yu-Xiang Liu, Yuan Wu

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.7field-weighted citation impact, top 29% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 7 citations in OpenAlex.

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

5 authors at 2 institutions in 2 countries.

Jian-Li DuanSchool of Information and Communication Engineering, Dalian Maritime University, Dalian 116026, China.ORCID 0000-0002-2206-676X
Bin LinSchool of Information and Communication Engineering, Dalian Maritime University, Dalian 116026, China.
Lin X CaiDepartment of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA.
Yu-Xiang LiuSchool of Information and Communication Engineering, Dalian Maritime University, Dalian 116026, China.
Yuan WuSchool of Science, Macao University, Macao 999078, China.
Dalian Maritime University · CNIllinois Institute of Technology · US

Funding

Dalian Science and Technology Innovation Fund 2019J11CY015National Natural Science Foundation of China 51939001National Natural Science Foundation of China 61971083
6 · The paper itself

Abstract

The increasing demands for real-time marine monitoring call for the wide deployment of Marine Monitoring Networks (MMNs). The low-rate underwater communications over a long distance, long propagation delay of underwater acoustic channel, and high deployment costs of marine sensors in a large-scale three-dimensional space bring great challenges in the network deployment and management of MMN. In this paper, we first propose a multitier, hierarchical network architecture of MMN with the support of edge computing (HMMN-EC) to enable efficient monitoring services in a harsh marine environment, taking into consideration the salient features of marine communications. Specifically, HMMN-EC is composed of three subnetworks, i.e., underwater acoustic subnetwork, the sea-surface wireless subnetwork, and the air wireless subnetwork, with a diversity of network nodes with different capabilities. We then jointly investigate the deployment diverse network nodes with various constraints in different subnetworks of HMMN-EC. To this end, we formulate a Multiobjective Optimization (MO) problem to minimize the network deployment cost while achieving the maximal network lifetime, subject to the limited energy of different marine nodes and the complex deployment environment. To solve the formulated problem, we present an Ant-Colony-based Efficient Topology Optimization (AC-ETO) algorithm to find the optimal locations of nodes in different subnetworks of MMN in a large-scale deployment. The time complexity of the proposed algorithm is also analyzed. Finally, extensive simulations are carried out to validate the superior performance of the proposed algorithm compared with some existing solutions.

Indexed as

ant colony algorithmgurobimarine monitoring networksmultiobjective optimizationnetwork deployment

Identifiers

PMID32796557
PMCPMC7472283
OpenAlexW3048404200

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.