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Dynamic Ontology-Based Sensor Binding

  • Pascal Hirmer
  • Matthias Wieland
  • Uwe Breitenbücher
  • Bernhard Mitschang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9809)

Abstract

In recent years, the Internet of Things gains more and more attention through cheap hardware devices and, consequently, an increased interconnection of them. These devices equipped with sensors and actuators form the foundation for so called smart environments that enable monitoring as well as self-organization. However, an efficient sensor registration, binding, and sensor data provisioning is still a major issue for the Internet of Things. Usually, these steps can take up to days or even weeks due to a manual configuration and binding by sensor experts that furthermore have to communicate with domain-experts that define the requirements, e.g. the types of sensors, for the smart environments. In previous work, we introduced a first vision of a method for automated sensor registration, binding, and sensor data provisioning. In this paper, we further detai l and extend this vision, e.g., by introducing optimization steps to enhance efficiency as well as effectiveness. Furthermore, the approach is evaluated through a prototypical implementation.

Keywords

Internet of Things Sensors Ontologies Data provisioning 

Notes

Acknowledgment

This work is partially funded by the DFG project SitOPT (610872) and by the BMWi project SmartOrchestra (01MD16001F).

References

  1. 1.
    Aberer, K., Hauswirth, M., Salehi, A.: Zero-programming sensor network deployment. In: Proceedings of the Service Platforms for Future Mobile Systems (SAINT 2007) (2007)Google Scholar
  2. 2.
    Binz, T., Breitenbücher, U., Kopp, O., Leymann, F.: TOSCA: portable automated deployment and management of cloud applications. In: Bouguettaya, A., Sheng, Q.Z., Daniel, F. (eds.) Advanced Web Services, pp. 527–549. Springer, New York (2014)CrossRefGoogle Scholar
  3. 3.
    Gurgen, L., Roncancio, C., Labbé, C., Bottaro, A., Olive, V.: SStreaMWare: a service oriented middleware for heterogeneous sensor data management. In: International Conference on Pervasive Services (2008)Google Scholar
  4. 4.
    Hauswirth, M., Aberer, K.: Middleware support for the “Internet of Things”. In: 5th GI/ITG KuVS Fachgespräch “Drahtlose Sensornetze” (2006)Google Scholar
  5. 5.
    Hirmer, P., Wieland, M., Breitenbücher, U., Mitschang, B.: Automated sensor registration, binding and sensor data provisioning. In: Proceedings of the CAiSE 2016 Forum at the 28th International Conference on Advanced Information Systems Engineering (2016). Accepted for publicationGoogle Scholar
  6. 6.
    Hirmer, P., Wieland, M., Schwarz, H., Mitschang, B., Breitenbücher, U., Leymann, F.: SitRS - a situation recognition service based on modeling and executing situation templates. IBM Research Report (2015)Google Scholar
  7. 7.
    Ishaq, I., Hoebeke, J., Rossey, J., De Poorter, E., Moerman, I., Demeester, P.: Facilitating sensor deployment, discovery and resource access using embedded web services. In: 2012 Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), pp. 717–724, July 2012Google Scholar
  8. 8.
    Jazdi, N.: Cyber physical systems in the context of Industry 4.0. In: 2014 IEEE International Conference on Automation, Quality and Testing, Robotics (2014)Google Scholar
  9. 9.
    Kassner, L.B., Mitschang, B.: MaXCept-Decision Support in exception handling through unstructured data integration in the production context. an integral part of the smart factory. In: Proceedings of the 48th Hawaii International Conference on System Sciences (2015)Google Scholar
  10. 10.
    Lee, K.: IEEE 1451: a standard in support of smart transducer networking. In: Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference, IMTC 2000 (2000)Google Scholar
  11. 11.
    Li, F., Vögler, M., ClaeSSens, M., Dustdar, S.: Towards automated IoT application deployment by a cloud-based approach. In: 2013 IEEE 6th International Conference on Service-Oriented Computing and Applications, pp. 61–68, December 2013Google Scholar
  12. 12.
    Reiter, M., et al.: Quality of data driven simulation workflows. In: 2012 8th IEEE International Conference on e-Science (2012)Google Scholar
  13. 13.
    Russomanno, D.J., Kothari, C.R., Thomas, O.A.: Building a sensor ontology: a practical approach leveraging ISO and OGC models. In: IC-AI (2005)Google Scholar
  14. 14.
    Scerri, S., Attard, J., Rivera, I., Valla, M.: DCON: interoperable context representation for pervasive environments. In: AAAI Workshops (2012)Google Scholar
  15. 15.
    Saldatos, J., et al.: OpenIoT: open source Internet-of-Things in the cloud. In: Podnar Žarko, I., Pripužić, K., Serrano, M. (eds.) FP7 OpenIoT Project Workshop 2014. LNCS, vol. 9001, pp. 13–25. Springer, Heidelberg (2015)Google Scholar
  16. 16.
    Vermesan, O., Friess, P.: Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems. River Publishers, Aalborg (2013)Google Scholar
  17. 17.
    Vögler, M., Schleicher, J., Inzinger, C., Dustdar, S.: A scalable framework for provisioning large-scale IoT deployments. ACM Trans. Internet Technol. 16(2), 11:1–11:20 (2016). http://doi.acm.org/10.1145/2850416 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Pascal Hirmer
    • 1
  • Matthias Wieland
    • 1
  • Uwe Breitenbücher
    • 2
  • Bernhard Mitschang
    • 1
  1. 1.Institute of Parallel and Distributed SystemsUniversity of StuttgartStuttgartGermany
  2. 2.Institute of Architecture of Application SystemsUniversity of StuttgartStuttgartGermany

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