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

Author:

Gallego-Madrid JorgeORCID,Molina-Zarca AlejandroORCID,Sanchez-Iborra RamonORCID,Bernal-Bernabe JorgeORCID,Santa JoséORCID,Ruiz Pedro MiguelORCID,Skarmeta-Gómez Antonio F.ORCID

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.

Funder

AXA Research Fund

BBVA Foundation

European Commission

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A 3D simulation framework with ray-tracing propagation for LoRaWAN communication;Internet of Things;2023-12

2. Decomposition-based learning in drone-assisted wireless-powered mobile edge computing networks;Digital Communications and Networks;2023-11

3. Data collection from LoRaWAN sensor network by UAV gateway: design, empirical results and dataset;2023 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit);2023-06-06

4. LoRa Technology in Flying Ad Hoc Networks: A Survey of Challenges and Open Issues;Sensors;2023-02-21

5. Supporting Path Planning in LoRa-based UAVs for dynamic Coverage for IoT devices;2023 IEEE 20th Consumer Communications & Networking Conference (CCNC);2023-01-08

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3