An architecture for context-aware reactive systems based on run-time semantic models

In recent years, new classes of highly dynamic, complex systems are gaining momentum. 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. These classes include, but are not limited to IoT, smart cities, cyber-physical systems and sensor networks. An important design feature of these systems should be the ability of adapting their behavior to environment changes. This requires handling a runtime representation of the context enriched with variation points that relate different behaviors to possible changes of the representation. In this paper, we present a reference architecture for reactive, context-aware systems able to handle contextual knowledge (that defines what the system perceives) by means of virtual sensors and able to react to environment changes by means of virtual actuators, both represented in a declarative manner through semantic web technologies. To improve the ability to react with a proper behavior to context changes (e.g. faults) that may influence the ability of the system to observe the environment, we allow the definition of logical sensors and actuators through an extension of the SSN ontology (a W3C standard). In our reference architecture a knowledge base of sensors and actuators (hosted by an RDF triple store) is bound to real world by grounding semantic elements to physical devices via REST APIs. The proposed architecture along with the defined ontology try to address the main problems of dynamically reconfigurable 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.