Universitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica
Universitat Politècnica de Catalunya. WNG - Grup de xarxes sense fils
2024-06-27
In the dynamic landscape of Industry 4.0, robust wireless connectivity emerges as a critical enabler for Industrial Internet of Things (IIoT) applications. With the advent of Wi-Fi 7’s multilink operation (MLO), the demand for schedulers capable of meeting diverse Service Level Agreement (SLA) requirements within industrial environments becomes paramount. Addressing this need, this paper introduces Cooperative SLA-MLO (C-SLA-MLO), a novel distributed multilink scheduler that balances data across MLO channels to fulfill the SLA of STAs operating within the same BSS. We provide a simulation-based evaluation where we compare C-SLAMLO with other benchmark approaches, in terms of SLA compliance when varying the SLA characteristics, the level of QoS, or background traffic, showcasing an average reduction of 90% in SLA deviation in the industrial use case. This study contributes practical insights for enhancing wireless connectivity in IIoT, offering potential benefits for industrial network optimization by exploiting the MLO feature brought by the new IEEE 802.11be.
This work is supported by the EU’s H2020 5GSmartFact project under the MSCA, Spain grant agreement ID 956670. This work was also partly supported by the Spanish the MCIN/AEI, Spain/ 10.13039/501100011050 through project PID2019-106808RA-I00 and MINECO, Spain and EU PRTR UNICO I+D number TSI-063000-2021-15-6GSMART-EZ.
Postprint (published version)
Article
English
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors; Multilink operation; IEEE 802.11be; SLAs; Wi-Fi 7
Elsevier
https://www.sciencedirect.com/science/article/pii/S2542660524002105
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-106808RA-I00/ES/RED MALLADA IOT CON RADIO DE BAJA POTENCIA/
info:eu-repo/grantAgreement/EC/H2020/956670/EU/Industrial Doctorate Training Network on Future Wireless Connected and Automated Industry enabled by 5G/5GSmartFact
http://creativecommons.org/licenses/by-nc-nd/4.0/
Open Access
Attribution-NonCommercial-NoDerivatives 4.0 International
E-prints [72986]