TY - GEN
T1 - Demonstrating Wi-Fi Slicing Capabilities for Enhancing Performance of Industrial Applications
AU - Limani, Xhulio
AU - Slamnik-Krijestorac, Nina
AU - Miranda, Gilson
AU - Bostani, Ali
AU - Shen, Xiaoman
AU - Pan, Chun
AU - Jiang, Xingfeng
AU - Zhang, Chi
AU - Marquez-Barja, Johann M.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024/3/18
Y1 - 2024/3/18
N2 - In the rapidly evolving Industry 4.0 landscape, the integration of industrial robots and Artificial Intelligence (AI) is revolutionizing the processes involved in storing and managing goods. While these advancements hold the promise of enhancing operational efficiency, they necessitate a robust and high-performing indoor network infrastructure. This demo paper introduces a dynamic network slicing mechanism tailored for Wi-Fi networks, capitalizing on readily available Commercial Off-The-Shelf (COTS) devices, and seamlessly incorporating In-Band Network Telemetry (INT) within a Software Defined Networking (SDN) framework. To effectively navigate the intricacies and uncertainties of network environments, we employ Fuzzy Logic to oversee queueing disciplines (qdisc), which directly influence air-time - the duration a device allocates to transmitting or receiving data over a wireless channel. Through a series of experimental demonstrations, we highlight the effectiveness of our proposed mechanism in maintaining stringent Quality of Service (QoS) standards even in conditions of network saturation.
AB - In the rapidly evolving Industry 4.0 landscape, the integration of industrial robots and Artificial Intelligence (AI) is revolutionizing the processes involved in storing and managing goods. While these advancements hold the promise of enhancing operational efficiency, they necessitate a robust and high-performing indoor network infrastructure. This demo paper introduces a dynamic network slicing mechanism tailored for Wi-Fi networks, capitalizing on readily available Commercial Off-The-Shelf (COTS) devices, and seamlessly incorporating In-Band Network Telemetry (INT) within a Software Defined Networking (SDN) framework. To effectively navigate the intricacies and uncertainties of network environments, we employ Fuzzy Logic to oversee queueing disciplines (qdisc), which directly influence air-time - the duration a device allocates to transmitting or receiving data over a wireless channel. Through a series of experimental demonstrations, we highlight the effectiveness of our proposed mechanism in maintaining stringent Quality of Service (QoS) standards even in conditions of network saturation.
KW - Airtime
KW - Fuzzy Logic
KW - In-band Network Telemetry
KW - Network Slicing
KW - Testbed
KW - Wi-Fi
UR - http://www.scopus.com/inward/record.url?scp=85189210010&partnerID=8YFLogxK
U2 - 10.1109/CCNC51664.2024.10454645
DO - 10.1109/CCNC51664.2024.10454645
M3 - Conference contribution
AN - SCOPUS:85189210010
T3 - Proceedings - IEEE Consumer Communications and Networking Conference, CCNC
SP - 1122
EP - 1123
BT - 2024 IEEE 21st Consumer Communications and Networking Conference, CCNC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st IEEE Consumer Communications and Networking Conference, CCNC 2024
Y2 - 6 January 2024 through 9 January 2024
ER -