EdgeP4: A P4-Programmable Edge Intelligent Ethernet Switch for Tactile Cyber-Physical Systems

TL;DR

This paper introduces two P4-programmable edge algorithms for tactile cyber-physical systems that reduce latency and network load by locally computing control signals, enhancing real-time responsiveness and efficiency.

Contribution

The paper presents novel edge intelligence algorithms implemented on P4 switches that enable local control in tactile systems, significantly reducing latency and network traffic.

Findings

Round trip time for pose correction is less than 100 microseconds.

Tremor suppression reduces network load by up to 99.9%.

Algorithms enable seamless switching based on task requirements.

Abstract

Tactile Internet based operations, e.g., telesurgery, rely on end-to-end closed loop control for accuracy and corrections. The feedback and control are subject to network latency and loss. We design two edge intelligence algorithms hosted at P4 programmable end switches. These algorithms locally compute and command corrective signals, thereby dispense the feedback signals from traversing the network to the other ends and save on control loop latency and network load. We implement these algorithms entirely on data plane on Netronome Agilio SmartNICs using P4. Our first algorithm, $\textit{pose correction}$, is placed at the edge switch connected to an industrial robot gripping a tool. The round trip between transmitting force sensor array readings to the edge switch and receiving correct tip coordinates at the robot is shown to be less than $100~\mu s$. The second algorithm, $\textit{tremor suppression}$, is placed at the edge switch connected to the human operator. It suppresses physiological tremors of amplitudes smaller than $100~\mu m$ which not only improves the application's performance but also reduces the network load up to $99.9\%$. Our solution allows edge intelligence modules to seamlessly switch between the algorithms based on the tasks being executed at the end hosts.