The overlap of the two established fields of cyber-physical systems and self-aware computing hosts systems with noteworthy autonomous properties situated in complex, dynamic environments, that must satisfy multiple, possibly conflicting constraints (e.g., performance, timeliness, energy, reliability). Self-aware cyber-physical systems are situated in dynamic physical environments and constrained in their resources, they understand their own state and that of their environment. Based on that understanding, they are able to make appropriate decisions autonomously at runtime with high efficiency.
We will review the state of the art of this exciting domain, and the tutorial will be structured as follows:
– Comprehensive Observation: The processing of sensory data is accompanied with the collection of meta data that allows for assessing the quality of the observations, their relevance and their abstraction into the semantic domain of the goals of the systems. We show how applying simple strategies regarding this fundamental aspect can lead to significant improvements in performance of the system, in particular regarding its reliability and resource efficiency.
– Situatedness: The system is always in a physical situation relating its body to environmental bodies. It lives through and keeps track of a sequence of situations. Hence, the system is keenly aware of spatial and time relations between its body and its environment. Spatial relations are based on absolute (a coordinate system) and/or relative (right, left, above, below, …) relations. The time
relations are also based on absolute (some world time) and/or relative (earlier, ater, …) relations and imply real-time properties. Within this tutorial, we will also shed light on other forms of relations in which a system can be situated.
– Computational self-awareness: Computational self-awareness has a dual role in self-* systems. On the one hand it provides a foundation for these self-* properties, as it is concerned with getting the right self-knowledge to inform other self-* behaviours. On the other hand, it also provides a meta-reasoning layer above them, in order to guide effective self-* behaviour. We will review role and
benefits of computational self-awareness in resource constrained CPS.
– Self-* in Embodied CPS: Neurorobotics views the embodiment as central to the behavior and learning of a robot including its shape and materials. In this part of the tutorial we will connect to neurorobotics and similar lines of research including “morphological computation” in which processes are performed by the body and its exploitation of the environment, in the service of a holistic approach that balances the physical body and central control.
Axel Jantsch (TU Wien, Austria), Peter Lewis (Aston University, UK), Nima Taherinejad (TU Wien, Austria), Nikil Dutt (UC Irvine, USA), and Lukas Esterle (Aston University, UK)
Researcher who have a background in self-aware or autonomic computing but are not familiar with embedded and cyber-physical systems, and the implications on resource constraints, real-time behavior and situatedness. Or, researchers who are familar with embedded and cyber-physical systems but have no clear understanding of the concepts of self-awareness.