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  • articleNo Access

    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.

  • chapterNo Access

    Bioinspired Neural Model of the Semantic Content

    The paper started from the premise that semantic structures can be identified in natural language at the neural level and investigated the possibility of implementing such a structure using self-organizing maps (SOMs). The phonemes are the fundamental units that contribute according to an underlying dynamic process to the formation of meaning as a whole. The dynamic process of the formation of words was simulated by the enfoldment of the SOMs of the component phonemes. The resultant SOM serves as the meaning carrying structure at the word level.