Evidence map›Paper›PMID 34204293›Full record

ArticleSensors (Basel, Switzerland)2021

Improved Recursive DV-Hop Localization Algorithm with RSSI Measurement for Wireless Sensor Networks.

Sana Messous, Hend Liouane, Omar Cheikhrouhou, Habib Hamam

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

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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

4 authors.

Sana MessousResearch Laboratory of Automatic Signal and Image Processing (LARATSI), National Engineering School of Monastir (ENIM), 5019 Monastir, Department of Electrical Engineering, University of Monastir, Monastir, Tunisia.ORCID 0000-0002-3337-1794
Hend LiouaneResearch Laboratory of Automatic Signal and Image Processing (LARATSI), National Engineering School of Monastir (ENIM), 5019 Monastir, Department of Electrical Engineering, University of Monastir, Monastir, Tunisia.
Omar CheikhrouhouDepartment of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.ORCID 0000-0002-9898-3898
Habib HamamElectrical Engineering, Faculty of Engineering, Moncton University, Moncton, NB E1A3E9, Canada.ORCID 0000-0002-5320-1012

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As localization represents the main backbone of several wireless sensor networks applications, several localization algorithms have been proposed in the literature. There is a growing interest in the multi-hop localization algorithms as they permit the localization of sensor nodes even if they are several hops away from anchor nodes. One of the most famous localization algorithms is the Distance Vector Hop (DV-Hop). Aiming to minimize the large localization error in the original DV-Hop algorithm, we propose an improved DV-Hop algorithm in this paper. The distance between unknown nodes and anchors is estimated using the received signal strength indication (RSSI) and the polynomial approximation. Moreover, the proposed algorithm uses a recursive computation of the localization process to improve the accuracy of position estimation. Experimental results show that the proposed localization technique minimizes the localization error and improves the localization accuracy.

Indexed as

DV-Hoplocalizationlocalization accuracymulti-hop algorithmsonline sequential computationRSSI

Identifiers

PMID34204293
PMCPMC8233725

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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.