Introducing k4.0s: a Model for Mixed-Criticality Container Orchestration in Industry 4.0 (extended)

TL;DR

This paper introduces k4.0s, a novel orchestration model for Industry 4.0 that ensures time predictability and mixed-criticality support in edge cloud environments, addressing limitations of current solutions.

Contribution

The paper presents a new model for mixed-criticality container orchestration that incorporates timeliness, criticality, and network requirements, with a Kubernetes-based implementation.

Findings

Node assurance levels are essential for mixed-criticality workloads.

Effective monitoring strategies are crucial for time-predictable orchestration.

The proposed model improves support for real-time and mixed-criticality applications.

Abstract

Time predictable edge cloud is seen as the answer for many arising needs in Industry 4.0 environments, since it is able to provide flexible, modular, and reconfigurable services with low latency and reduced costs. Orchestration systems are becoming the core component of clouds since they take decisions on the placement and lifecycle of software components. Current solutions start introducing real-time containers support for time predictability; however, these approaches lack of determinism as well as support for workloads requiring multiple levels of assurance/criticality. In this paper, we present k4.0s, an orchestration model for real-time and mixed-criticality environments, which includes timeliness, criticality and network requirements. The model leverages new abstractions for both node and jobs, e.g., node assurance, and requires novel monitoring strategies. We sketch an implementation of the proposal based on Kubernetes, and present an experimentation motivating the need for node assurance levels and adequate monitoring.