Evidence map›Paper›PMID 32718087›Full record

ArticleSensors (Basel, Switzerland)2020

Enhancing Extensive and Remote LoRa Deployments through MEC-Powered Drone Gateways.

Jorge Gallego-Madrid, Alejandro Molina-Zarca, Ramon Sanchez-Iborra, Jorge Bernal-Bernabe, José Santa, Pedro Miguel Ruiz, Antonio F Skarmeta-Gómez

Abstract 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. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

7 authors.

Jorge Gallego-MadridDepartment of Information and Communication Engineering, University of Murcia, 30100 Murcia, Spain.ORCID 0000-0001-9429-8634
Alejandro Molina-ZarcaDepartment of Information and Communication Engineering, University of Murcia, 30100 Murcia, Spain.ORCID 0000-0003-0038-9012
Ramon Sanchez-IborraDepartment of Information and Communication Engineering, University of Murcia, 30100 Murcia, Spain.ORCID 0000-0002-0069-3017
Jorge Bernal-BernabeDepartment of Information and Communication Engineering, University of Murcia, 30100 Murcia, Spain.ORCID 0000-0002-7538-4788
José SantaDepartment of Electronics, Computer Technology and Projects, Technical University of Cartagena, 30202 Cartagena, Spain.ORCID 0000-0001-9224-7112
Pedro Miguel RuizDepartment of Information and Communication Engineering, University of Murcia, 30100 Murcia, Spain.ORCID 0000-0002-2263-1327
Antonio F Skarmeta-GómezDepartment of Information and Communication Engineering, University of Murcia, 30100 Murcia, Spain.ORCID 0000-0002-5525-1259

Funding

AXA Research Fund AXA Postdoctoral Scholarship (Cyber-SecIoT)BBVA Foundation 2018 Leonardo Grant for Researchers and Cultural CreatorsEuropean Commission IoTCrawler (Grant No. 7798520)European Commission Pharaon (Grant No. 857188)Spanish Ministry of Science, Innovation and Universities PERSEIDES (Grant No.TIN2017-86885-R)Spanish Ministry of Science, Innovation and Universities Ramon y Cajal Program (Grant No. RYC-2017-23823)
6 · The paper itself

Abstract

The distribution of Internet of Things (IoT) devices in remote areas and the need for network resilience in such deployments is increasingly important in smart spaces covering scenarios, such as agriculture, forest, coast preservation, and connectivity survival against disasters. Although Low-Power Wide Area Network (LPWAN) technologies, like LoRa, support high connectivity ranges, communication paths can suffer from obstruction due to orography or buildings, and large areas are still difficult to cover with wired gateways, due to the lack of network or power infrastructure. The proposal presented herein proposes to mount LPWAN gateways in drones in order to generate airborne network segments providing enhanced connectivity to sensor nodes wherever needed. Our LoRa-drone gateways can be used either to collect data and then report them to the back-office directly, or store-carry-and-forward data until a proper communication link with the infrastructure network is available. The proposed architecture relies on Multi-Access Edge Computing (MEC) capabilities to host a virtualization platform on-board the drone, aiming at providing an intermediate processing layer that runs Virtualized Networking Functions (VNF). This way, both preprocessing or intelligent analytics can be locally performed, saving communications and memory resources. The contribution includes a system architecture that has been successfully validated through experimentation with a real test-bed and comprehensively evaluated through computer simulation. The results show significant communication improvements employing LoRa-drone gateways when compared to traditional fixed LoRa deployments in terms of link availability and covered areas, especially in vast monitored extensions, or at points with difficult access, such as rugged zones.

Indexed as

dronesLoRAWANLPWANMECNFV

Identifiers

PMID32718087
PMCPMC7435977

What OpenQuestion holds

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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.