In this chapter we present the Zones-of-Influence Framework, a software solution for enabling spatial awareness of autonomous embedded systems. It is based on the concepts presented in previous chapters, in particular the qualitative abstraction of spatial relations and the rule-based reasoning about them, and has been designed to facilitate the development of spatially aware applications for autonomous and spontaneously interacting systems. First, Section 6.1 presents design considerations for and an overview of the framework architecture, which has been developed with flexibility, modularity, efficiency and scalability in mind. It is split into components for the discovery of artifacts and the exchange of self-descriptions with them, the maintenance of a Zones-of-Influence model with the spatial properties of discovered artifacts, the application-dependent recognition and qualitative abstraction of spatial relations as well as the rule-based reasoning about qualitative relations over time in order to infer new relations or trigger according applicationlevel actions. An overview of these components – which provide spatial awareness to the application level – is given in Section 6.2, including a detailed description of their interfaces and relevant implementation-specific issues. The results of performance tests are presented in Section 6.3, which have been carried out in order to evaluate the runtime efficiency and scalability of the framework implementation; a qualitative evaluation by means of multiple application scenarios will be given afterwards in Chapter 7. Finally, Section 6.4 discusses features and properties of the framework and identifies open issues for future work. The development of the Zones-of-Influence Framework architecture and its implementation have been conducted in an industrial research project [FDE+08] with Siemens AG Germany.
KeywordsRelationship Recognition Framework Architecture Callback Method Rule Engine Digital Artifact
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