Demonstrating Wi-Fi Slicing Capabilities for Enhancing Performance of Industrial Applications

Abstract

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. Our solution guarantees uninterrupted and streamlined operations, even in high-demand scenarios