Study of the Efficiency of Fog Computing in an Optimized LoRaWAN Cloud Architecture
Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic
Typ dokumentu časopisecké články
Grantová podpora
SP2021/25
Ministerstvo Školství, Mládeže a Tělovýchovy
LM2018140
e-Infrastructure CZ
PubMed
34063234
PubMed Central
PMC8125713
DOI
10.3390/s21093159
PII: s21093159
Knihovny.cz E-zdroje
- Klíčová slova
- LoRaWAN, cloud computing, fog computing, internet of things, network architecture, simulation,
- Publikační typ
- časopisecké články MeSH
The technologies of the Internet of Things (IoT) have an increasing influence on our daily lives. The expansion of the IoT is associated with the growing number of IoT devices that are connected to the Internet. As the number of connected devices grows, the demand for speed and data volume is also greater. While most IoT network technologies use cloud computing, this solution becomes inefficient for some use-cases. For example, suppose that a company that uses an IoT network with several sensors to collect data within a production hall. The company may require sharing only selected data to the public cloud and responding faster to specific events. In the case of a large amount of data, the off-loading techniques can be utilized to reach higher efficiency. Meeting these requirements is difficult or impossible for solutions adopting cloud computing. The fog computing paradigm addresses these cases by providing data processing closer to end devices. This paper proposes three possible network architectures that adopt fog computing for LoRaWAN because LoRaWAN is already deployed in many locations and offers long-distance communication with low-power consumption. The architecture proposals are further compared in simulations to select the optimal form in terms of total service time. The resulting optimal communication architecture could be deployed to the existing LoRaWAN with minimal cost and effort of the network operator.
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Santamaria A.F., De Rango F., Serianni A., Raimondo P. A real IoT device deployment for e-Health applications under lightweight communication protocols, activity classifier and edge data filtering. Comput. Commun. 2018;128:60–73. doi: 10.1016/j.comcom.2018.06.010. DOI
Santamaria A.F., Raimondo P., Tropea M., De Rango F., Aiello C. An IoT Surveillance System Based on a Decentralised Architecture. Sensors. 2019;19:1469. doi: 10.3390/s19061469. PubMed DOI PMC
De Rango F., Tropea M., Fazio P. Mitigating DoS attacks in IoT EDGE Layer to preserve QoS topics and nodes’ energy; Proceedings of the IEEE INFOCOM 2020-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS); Toronto, ON, Canada. 6–9 July 2020; pp. 842–847.
Jalowiczor J., Gresak E., Rezac F., Rozhon J., Safarik J. Autonomous Systems: Sensors, Processing, and Security for Vehicles and Infrastructure. SPIE; Bellingham, WA, USA: 2019. Development and deployment of the main parts of LoRaWAN private network.
Dillon T., Wu C., Chang E. Cloud Computing: Issues and Challenges; Proceedings of the 2010 24th IEEE International Conference on Advanced Information Networking and Applications; Perth, Australia. 20–23 April 2010; pp. 27–33.
Puliafito C., Mingozzi E., Longo F., Puliafito A., Rana O. Fog Computing for the Internet of Things. ACM Trans. Internet Technol. 2019;19:1–41. doi: 10.1145/3301443. DOI
Shi W., Cao J., Zhang Q., Li Y., Xu L. Edge Computing: Vision and Challenges. IEEE Internet Things J. 2016;3:637–646. doi: 10.1109/JIOT.2016.2579198. DOI
Ikpehai A., Adebisi B., Rabie K.M., Anoh K., Ande R.E., Hammoudeh M., Gacanin H., Mbanaso U.M. Low-Power Wide Area Network Technologies for Internet-of-Things: A Comparative Review. IEEE Internet Things J. 2019;6:2225–2240. doi: 10.1109/JIOT.2018.2883728. DOI
Ballerini M., Polonelli T., Brunelli D., Magno M., Benini L. NB-IoT Versus LoRaWAN: An Experimental Evaluation for Industrial Applications. IEEE Trans. Ind. Inform. 2020;16:7802–7811. doi: 10.1109/TII.2020.2987423. DOI
OpenFog Consortium Architecture Working Group . Openfog Reference Architecture for Fog Computing. 2017. [(accessed on 28 April 2021)]. pp. 1–162. Technical Report. Available online: https://inf.mit.bme.hu/sites/default/files/materials/category/kateg%C3%B3ria/oktat%C3%A1s/msc-t%C3%A1rgyak/kiberfizikai-rendszerek/17/07_OpenFog.pdf.
Yi S., Hao Z., Qin Z., Li Q. Fog Computing: Platform and Applications; Proceedings of the 2015 Third IEEE Workshop on Hot Topics in Web Systems and Technologies (HotWeb); Washington, DC, USA. 12–13 November 2015; pp. 73–78.
Yi S., Li C., Li Q. A Survey of Fog Computing; Proceedings of the 2015 Workshop on Mobile Big Data—Mobidata ’15; Hangzhou, China. 21 June 2015; New York, NY, USA: ACM Press; 2015. pp. 37–42.
Naha R.K., Garg S., Georgakopoulos D., Jayaraman P.P., Gao L., Xiang Y., Ranjan R. Fog Computing: Survey of Trends, Architectures, Requirements, and Research Directions. IEEE Access. 2018;6:47980–48009. doi: 10.1109/ACCESS.2018.2866491. DOI
Mouradian C., Naboulsi D., Yangui S., Glitho R.H., Morrow M.J., Polakos P.A. A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges. IEEE Commun. Surv. Tutor. 2018;20:416–464. doi: 10.1109/COMST.2017.2771153. DOI
Chiang M., Zhang T. Fog and IoT: An Overview of Research Opportunities. IEEE Internet Things J. 2016;3:854–864. doi: 10.1109/JIOT.2016.2584538. DOI
Roman R., Lopez J., Mambo M. Mobile edge computing, Fog et al: A survey and analysis of security threats and challenges. Future Gener. Comput. Syst. 2018;78:680–698. doi: 10.1016/j.future.2016.11.009. DOI
Alrawais A., Alhothaily A., Hu C., Cheng X. Fog Computing for the Internet of Things: Security and Privacy Issues. IEEE Internet Comput. 2017;21:34–42. doi: 10.1109/MIC.2017.37. DOI
Oh Y., Lee J., Kim C.-K. TRILO: A Traffic Indication-Based Downlink Communication Protocol for LoRaWAN. Wirel. Commun. Mob. Comput. 2018;2018:1–14. doi: 10.1155/2018/6463097. DOI
Lim J.-T., Han Y. Spreading Factor Allocation for Massive Connectivity in LoRa Systems. IEEE Commun. Lett. 2018;22:800–803. doi: 10.1109/LCOMM.2018.2797274. DOI
Sallum E., Pereira N., Alves M., Santos M. Improving Quality-Of-Service in LoRa Low-Power Wide-Area Networks through Optimized Radio Resource Management. J. Sens. Actuator Netw. 2020;9:10. doi: 10.3390/jsan9010010. DOI
Gia T.N., Jiang M., Rahmani A.-M., Westerlund T., Liljeberg P., Tenhunen H. Fog Computing in Healthcare Internet of Things: A Case Study on ECG Feature Extraction; Proceedings of the 2015 IEEE International Conference on Computer and Information Technology; Liverpool, UK. 26–28 October 2015; pp. 356–363.
Naranjo P.G.V., Pooranian Z., Shojafar M., Conti M., Buyya R. FOCAN: A Fog-supported smart city network architecture for management of applications in the Internet of Everything environments. J. Parallel Distrib. Comput. 2019;132:274–283. doi: 10.1016/j.jpdc.2018.07.003. DOI
Gupta H., Vahid Dastjerdi A., Ghosh S.K., Buyya R. IFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments. Softw. Pract. Exp. 2017;47:1275–1296. doi: 10.1002/spe.2509. DOI
Mahmud R., Srirama S.N., Ramamohanarao K., Buyya R. Quality of Experience (QoE)-aware placement of applications in Fog computing environments. J. Parallel Distrib. Comput. 2019;132:190–203. doi: 10.1016/j.jpdc.2018.03.004. DOI
Mekki K., Bajic E., Chaxel F., Meyer F. A comparative study of LPWAN technologies for large-scale IoT deployment. ICT Express. 2019;5:1–7. doi: 10.1016/j.icte.2017.12.005. DOI
Fraga-Lamas P., Celaya-Echarri M., Lopez-Iturri P., Castedo L., Azpilicueta L., Aguirre E., Suárez-Albela M., Falcone F., Fernández-Caramés T.M. Design and Experimental Validation of a LoRaWAN Fog Computing Based Architecture for IoT Enabled Smart Campus Applications. Sensors. 2019;19:3287. doi: 10.3390/s19153287. PubMed DOI PMC
Barro P.A., Zennaro M., Degila J., Pietrosemoli E. A Smart Cities LoRaWAN Network Based on Autonomous Base Stations (BS) for Some Countries with Limited Internet Access. Future Internet. 2019;11:93. doi: 10.3390/fi11040093. DOI
Sisinni E., Carvalho D.F., Ferrari P. Emergency Communication in IoT Scenarios by Means of a Transparent LoRaWAN Enhancement. IEEE Internet Things J. 2020;7:10684–10694. doi: 10.1109/JIOT.2020.3011262. DOI
Froiz-Míguez I., Lopez-Iturri P., Fraga-Lamas P., Celaya-Echarri M., Blanco-Novoa Ó., Azpilicueta L., Falcone F., Fernández-Caramés T.M. Design, Implementation, and Empirical Validation of an IoT Smart Irrigation System for Fog Computing Applications Based on LoRa and LoRaWAN Sensor Nodes. Sensors. 2020;20:6865. doi: 10.3390/s20236865. PubMed DOI PMC
LoRaWAN™ 1.1 Specification. [(accessed on 13 February 2021)]; Available online: https://lora-alliance.org.
iC880A-SPI LoRa™ Concentrator. [(accessed on 1 February 2021)]; Available online: https://wireless-solutions.de.
Metzger F., Hobfeld T., Bauer A., Kounev S., Heegaard P.E. Modeling of Aggregated IoT Traffic and Its Application to an IoT Cloud. Proc. IEEE. 2019;107:679–694. doi: 10.1109/JPROC.2019.2901578. DOI