Evidence map›Paper›PMID 34883985›Full record

ArticleSensors (Basel, Switzerland)2021

RM-ADR: Resource Management Adaptive Data Rate for Mobile Application in LoRaWAN.

Khola Anwar, Taj Rahman, Asim Zeb, Inayat Khan, Mahdi Zareei, Cesar Vargas-Rosales

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 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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

6 authors.

Khola AnwarDepartment of Physical & Numerical Science, Qurtuba University of Science & Information Technology, Peshawar 25000, Pakistan.
Taj RahmanDepartment of Physical & Numerical Science, Qurtuba University of Science & Information Technology, Peshawar 25000, Pakistan.
Asim ZebDepartment of Computer Science, Abbottabad University of Science and Technology, Abbottabad 22500, Pakistan.
Inayat KhanDepartment of Computer Science, University of Buner, Buner 19290, Pakistan.ORCID 0000-0003-0895-9665
Mahdi ZareeiTecnologico de Monterrey, Escuela de Ingenieria y Ciencias, Monterry 64849, Mexico.ORCID 0000-0001-6623-1758
Cesar Vargas-RosalesTecnologico de Monterrey, Escuela de Ingenieria y Ciencias, Monterry 64849, Mexico.ORCID 0000-0003-1770-471X

Funding

Zayed University Cluster Research R20143
6 · The paper itself

Abstract

LoRaWAN is renowned and a mostly supported technology for the Internet of Things, using an energy-efficient Adaptive Data Rate (ADR) to allocate resources (e.g., Spreading Factor (SF)) and Transmit Power (TP) to a large number of End Devices (EDs). When these EDs are mobile, the fixed SF allocation is not efficient owing to the sudden changes caused in the link conditions between the ED and the gateway. As a result of this situation, significant packet loss occurs, increasing the retransmissions from EDs. Therefore, we propose a Resource Management ADR (RM-ADR) at both ED and Network Sides (NS) by considering the packet transmission information and received power to address this issue. Through simulation results, RM-ADR showed improved performance compared to the state-of-the-art ADR techniques. The findings indicate a faster convergence time by minimizing packet loss ratio and retransmission in a mobile LoRaWAN network environment.

Indexed as

Mobile ApplicationsWireless TechnologyComputer Simulationconvergence timeenergy consumptioninternet of thingsLoRaWANmobilityresource management

Identifiers

PMID34883985
PMCPMC8659466

What OpenQuestion holds

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Registered trials

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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.