Self-healing is an increasingly popular approach to ensure resiliency, that is, a proper adaptation to failures and attacks, in cyber-physical systems (CPS). A very promising way of achieving self-healing is through structural adaptation (SHSA), by adding and removing components, or even by changing their interaction, at runtime. SHSA has to be enabled and supported by the underlying platform, in order to minimize undesired interference during components exchange and to reduce the complexity of the application components. In this paper, we discuss architectural requirements and design decisions which enable SHSA in CPS. We propose a platform that facilitates structural adaptation and demonstrate its capabilities on an example from the automotive domain: a fault-tolerant system that estimates the state-of-charge (SoC) of the battery. The SHSA support of the SoC estimator is enhanced through the existence of an ontology, capturing the interrelations among the components and using this information at runtime for reconfiguration. Finally, we demonstrate the efficiency of our SHSA framework by deploying it in a real-world CPS prototype of a rover under sensor failure.
In Proc. of ISORC'17, the 19th IEEE International Symposium on Real-Time Computing, Toronta, Canada, May, 2017, IEEE.
*This work was partially supported by the Artemis EMC2 Award, the
NSF-Frontiers Cyber-Physical Heart Award, FWF-NFN RiSE Award,
FWF-DC LMCS Award, FFG Harmonia Award, FFG Em2Apps Award, and the
TUW CPPS-DK Award.