Towards Mission-Critical Control at the Edge and Over 5G

Abstract

With the emergence of industrial IoT and cloud computing, and the advent of 5G and edge clouds, there are ambitious expectations on elasticity, economies of scale, and fast time to market for demanding use cases in the next generation of ICT networks. Responsiveness and reliability of wireless communication links and services in the cloud are set to improve significantly as the concept of edge clouds is becoming more prevalent. To enable industrial uptake we must provide cloud capacity in the networks but also a sufficient level of simplicity and self-sustainability in the software platforms. In this paper, we present a research test-bed built to study mission-critical control over the distributed edge cloud. We evaluate system properties using a conventional control application in the form of a Model Predictive Controller. Our cloud platform provides the means to continuously operate our mission-critical application while seamlessly relocating computations across geographically dispersed compute nodes. Through our use of 5G wireless radio, we allow for mobility and reliably provide compute resources with low latency, at the edge. The primary contribution of this paper is a state-of-the art, fully operational test-bed showing the potential for merged IoT, 5G, and cloud. We also provide an evaluation of the system while operating a mission-critical application and provide an outlook on a novel research direction.

Control-over-the-cloud: A performance study for cloud-native, critical control systems

“…Our example process is the ball and beam, detailed in [15]. The ball and beam process is non-trivial, have many controller implementations, is observable and intuitive to evaluate, and can be compactly detailed.…”

Quality-Elasticity: Improved Resource Utilization, Throughput, and Response Times Via Adjusting Output Quality to Current Operating Conditions

“…The current alternative, which is to just let service performance and throughput suffer, makes deployment of e.g. mission-critical software impossible [28].…”

Model Predictive Control for Automated Vehicle Steering

“…Paper [24] presented research of edge cloud on the Internet of Things (IoT) where the Model Predictive Controller evaluates the system properties. The paper presented the potential of merging the IoT, 5G, and cloud computing with the efficiency of deploying the automatic control system for time-sensitive and mission-critical processes.…”