Latency-Aware Industrial Fog Application Orchestration with Kubernetes

Abstract

The benefit of fog computing to use local devices more efficiently and to reduce the latency and operation cost compared to cloud infrastructure is promising for industrial automation. Many industrial (control) applications have demanding real-time requirements and existing automation networks typically exhibit low-bandwidth links between sensing and computing devices. Fog applications in industrial automation contexts thus require that the amount of data transferred between sensing, computing and actuating devices, as well as latencies of control loops are minimized. To meet these requirements, this paper proposes a fog layer architecture that manages the computation and deployment of latency-aware industrial applications with Kubernetes, the prevalent container orchestration framework. The resulting fog layer dynamically solves the resource allocation optimization problem and then deploys distributed containerized applications to automation system networks. It achieves this in a non-intrusive manner, i.e. without actively modifying Kubernetes. Moreover it does not depend on proprietary protocols and infrastructure and is thus widely applicable and preferable to a vendor-specific solution. We compare the architecture with two alternative approaches that differ in the level of coupling to Kubernetes.