Edge-Computing-Enabled Low-Latency Communication for a Wireless Networked Control System

Abstract

This study proposes a novel strategy for enhancing low-latency control performance in Wireless Networked Control Systems (WNCSs) through the integration of edge computing. Traditional networked control systems require the receipt of raw data from remote sensors to enable the controller to generate an appropriate control command, a process that can result in substantial periodic communication traffic and consequent performance degradation in some applications. To counteract this, we suggest the use of edge computing to preprocess the raw data, extract the essential features, and subsequently transmit them. Additionally, we introduce an adaptive scheme designed to curtail frequent data traffic by adaptively modifying periodic data transmission based on necessity. This scheme is achieved by refraining from data transmission when a comparative analysis of the previously transmitted and newly generated data shows no significant change. The effectiveness of our proposed strategy is empirically validated through experiments conducted on a remote control system testbed using a mobile robot that navigates the road by utilizing camera information. Through leveraging edge computing, only 3.42% of the raw data was transmitted. Our adaptive scheme reduced the transmission frequency by 20%, while maintaining an acceptable control performance. Moreover, we conducted a comparative analysis between our proposed solution and the state-of-the-art communication framework, WebRTC technology. The results demonstrate that our method effectively reduces the latency by 58.16% compared to utilizing the WebRTC alone in a 5G environment. The experimental results confirm that our proposed strategy significantly improves the latency performance of a WNCS.