Semantics-Driven Programming of Self-Adaptive Reactive Systems

In recent years, new classes of highly dynamic, complex systems are gaining momentum. These classes include, but are not limited to IoT, smart cities, cyber-physical systems and sensor networks. These systems are characterized by the need to express behaviors driven by external and/or internal changes, i.e. they are reactive and context-aware. A desirable design feature of these systems is the ability of adapting their behavior to environment changes. In this paper, we propose an approach to support adaptive, reactive systems based on semantic runtime representations of their context, enabling the selection of equivalent behaviors, i.e. behaviors that have the same effect on the environment. The context representation and the related knowledge are managed by an engine designed according to a reference architecture and programmable through a declarative definition of sensors and actuators. The knowledge base of sensors and actuators (hosted by an RDF triplestore) is bound to the real world by grounding semantic elements to physical devices via REST APIs. The proposed architecture along with the defined ontology tries to address the main problems of dynamically re-configurable systems by exploiting a declarative, queryable approach to enable runtime reconfiguration with the help of (a) semantics to support discovery in heterogeneous environment, (b) composition logic to define alternative behaviors for variation points, (c) bi-causal connection life-cycle to avoid dangling links with the external environment. The proposal is validated in a case study aimed at designing an edge node for smart buildings dedicated to cultural heritage preservation.

Runtime Safety Assurance for Adaptive Cyber-Physical Systems

Cyber-Physical Systems (CPS) provide their functionality by the interaction of various subsystems. CPS usually operate in uncertain environments and are often safety-critical. The constituent systems are developed by different stakeholders, who – in most cases – cannot fully know the composing parts at development time. Furthermore, a CPS may reconfigure itself during runtime, for instance in order to adapt to current needs or to handle failures. The information needed for safety assurance is only available at composition or reconfiguration time. To tackle this assurance issue, the authors propose a set of contracts to describe components' safety attributes. The contracts are used to verify the safety robustness of the parts and build a safety case at runtime. The approach is applied to a use case in the automotive domain to illustrate the concepts. In particular, the authors demonstrate safety assurance at upgrade and reconfiguration on the example of ontology-based runtime reconfiguration (ORR). ORR substitutes a failed service by exploiting the implicit redundancy of a system.