Safety of fog-based industrial automation systems

Abstract

The Fog computing paradigm employing multiple technologies is expected to play a key role in a multitude of industrial applications by fulfilling futuristic requirements such as flexible and enhanced computing, storage, and networking capability closer to the field devices. While performance aspects of the Fog paradigm has been the central focus of researchers, safety aspects have not received enough attention so far. In this paper, we identify various safety challenges related to the Fog paradigm and provide specific safety design aspects as a step towards enhancing safety in industrial automation scenarios. We contextualize these ideas by invoking a distributed mobile robots use-case that can benefit from the use of the Fog paradigm. CCS CONCEPTS• Computer systems organization → Embedded and cyberphysical systems; Fault-tolerant network topologies; Robotics; Robotic autonomy.

Electric drives as fog nodes in a fog computing‐based industrial use case

“…The authors modified the hypervisor with a new scheduler based on a fixed-priority policy and a control loop to control the timing constraints of virtual machines. [23] addressed safety critical applications running in the fog and how the FCP must cater to these specific requirements.…”

Enhancing Fault Detection in Time Sensitive Networks using Machine Learning

“…A particular challenge has been to introduce flexibility in the configuration process while maintaining guaranteed safety performance. [19] [20] discuss fault tolerance and safety aspects of TSN as a key enabler for Fog computing [21]. [22] gives a very good overview of various challenges for TSN in the industrial automation context.…”

Safety-oriented flexible design of Autonomous Mobile Robot systems

“…2) Fog & Edge computing: Of late there has been considerable advances and research focus on mobile edge computing and fog computing paradigms [13] at performance level as well as with regard to safety assurance [14]. The goal is to reduce latency and processing time by designating tasks to an edge device that is closer to the sensors and actuators than a typical geographically distant centralised cloud server.…”

“…The paper describes a componentbased architecture that seamlessly bridges the gap between real-time robot control and a distributed, integrated system. Desai et al [14] provide an overview of safety in the Fog ecosystem while [22] talks about safety certification issues in the robotics domain.…”