Heterogeneous distributed systems, including the Internet of Things (IoT) or distributed cyber-physical systems (CPS), often su↵er a lack of interoperability and security, which hinders the wider deployment of such systems. Specifically, the di↵erent levels of security requirements and the heterogeneity in terms of communication models, for instance, point-to-point vs. publish-subscribe, are the example challenges of IoT and distributed CPS consisting of heterogeneous devices and applications. In this paper, we propose a working application programming interface (API) and runtime to enhance interoperability and security while addressing the challenges that stem from the heterogeneity in the IoT and distributed CPS. In our case study, we design and implement our application programming interface (API) design approach using opensource software, and with our working implementation, we evaluate the e↵ectiveness of our proposed approach. Our experimental results suggest that our approach can achieve both interoperability and security in the IoT and distributed CPS with a reasonably small overhead and better-managed software.
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Semantic Localization for IoT
Euclidean geometry and Newtonian time with floating point numbers are common computational models of the physical world. However, to achieve the kind of cyber-physical collaboration that arises in the IoT, such a literal representation of space and time may not be the best choice. In this chapter we survey location models from robotics, the internet, cyber-physical systems, and philosophy. The diversity in these models is justified by differing application demands and conceptualizations of space (spatial ontologies). To facilitate interoperability of spatial knowledge across representations,we propose a logical frameworkwherein a spatial ontology is defined as a model-theoretic structure. The logic language induced from a collection of such structures may be used to formally describe location in the IoT via semantic localization. Space-aware IoT services gain advantages for privacy and interoperability when they are designed for the most abstract spatial-ontologies as possible.We finish the chapter with definitions for open ontologies and logical inference.
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- Award ID(s):
- 1836601
- PAR ID:
- 10311565
- Editor(s):
- Pandey, R.
- Date Published:
- Journal Name:
- Semantic IoT: Theory and Applications, Studies in Computational Intelligence 941
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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