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, 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 100μs. The second algorithm, tremor suppression, is placed at the edge switch connected to the human operator. It suppresses physiological tremors of amplitudes smaller than 100μm 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.
Cite
@article{arxiv.2309.10383,
title = {EdgeP4: A P4-Programmable Edge Intelligent Ethernet Switch for Tactile Cyber-Physical Systems},
author = {Nithish Krishnabharathi Gnani and Joydeep Pal and Deepak Choudhary and Himanshu Verma and Soumya Kanta Rana and Kaushal Mhapsekar and T. V. Prabhakar and Chandramani Singh},
journal= {arXiv preprint arXiv:2309.10383},
year = {2023}
}