Evidence map›Paper›PMID 35341173›Full record

ArticleComputational intelligence and neuroscience2022

Towards Energy-Efficient and Delay-Optimized Opportunistic Routing in Underwater Acoustic Sensor Networks for IoUT Platforms: An Overview and New Suggestions.

Varun G Menon, Divya Midhunchakkaravarthy, Aaromal Sujith, Sonali John, Xingwang Li, Mohammad R Khosravi

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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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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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Varun G MenonDepartment of Computer Science and Engineering, Lincoln University College, Petaling Jaya 47301, Malaysia.ORCID https://orcid.org/0000-0002-3055-9900
Divya MidhunchakkaravarthyCenter of Postgraduate Studies, Lincoln University College, Petaling Jaya 47301, Malaysia.
Aaromal SujithDepartment of Computer Science and Engineering, SCMS School of Engineering and Technology, Ernakulam 683576, India.
Sonali JohnDepartment of Computer Science and Engineering, SCMS School of Engineering and Technology, Ernakulam 683576, India.
Xingwang LiSchool of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China.
Mohammad R KhosraviDepartment of Computer Engineering, Persian Gulf University, Bushehr, Iran.ORCID https://orcid.org/0000-0002-2029-5067

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In underwater acoustic sensor networks (UASNs), the reliable transfer of data from the source nodes located underwater to the destination nodes at the surface through the network of intermediate nodes is a significant challenge due to various unique characteristics of UASN such as continuous mobility of sensor nodes, increased propagation delay, restriction in energy, and heightened interference. Recently, the location-based opportunistic routing protocols seem to show potential by providing commendable quality of service (QoS) in the underwater environment. This study initially reviews all the latest location-based opportunistic routing protocols proposed for UASNs and discusses its possible limitations and challenges. Most of the existing works focus either on improving the QoS or on energy efficiency, and the few hybrid protocols that focus on both parameters are too complex with increased overhead and lack techniques to overcome communication voids. Further, this study proposes and discusses an easy-to-implement energy-efficient location-based opportunistic routing protocol (EELORP) that can work efficiently for various applications of UASN-assisted Internet of Underwater Things (IoUTs) platforms with reduced delay. We simulate the protocol in Aqua-Sim, and the results obtained show better performance than existing protocols in terms of QoS and energy efficiency.

Identifiers

PMID35341173
PMCPMC8947909

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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.