Advertisement

An Ontology-Based IoT Resource Model for Resources Evolution and Reverse Evolution

  • Shuai Zhao
  • Yang Zhang
  • Junliang Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7636)

Abstract

In view of the characteristics of Internet of Things (IoT), the current architectures could not effectively use and manage IoT resources and information. Numerous projects in the area of IoT have proposed architectures which aim at integrating geographically dispersed and internet interconnected heterogeneous Wireless Sensor and Actuator Networks (WSAN) systems into a homogeneous fabric for real world information and interaction. These architectures are faced with very similar problems in how to support the evolution of resources and maintain service continuity, how to integrate the data which comes from heterogeneous resources. To address these issues, this paper proposes a resource model supporting dynamic evolution and reverse evolution. The resource model uses Linked Data and extends the existing ontologies, such as W3C SSN, etc. This resource model can express domain knowledge, event rules, and support event-based reverse evolution. Based on the resource model, our SOA-based framework can automatically access resources, generate and interpret semantic context information, dynamically create resources, and interpret historical data and events. The validation of the resource model and framework is shown through the CCMWS (Coal mine comprehensive monitoring and early warning system).

Keywords

Semantic Model Resource Access Resource Model Heterogeneous Resource Reverse Evolution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Xing, L., Jin, Z., Li, G.: Modeling and verifying services of Internet of Things based on timed automata. Chinese Journal of Computers 34(8), 1365–1377 (2011) (in Chinese)CrossRefGoogle Scholar
  2. 2.
    Villalonga, C., Bauer, M., López Aguilar, F., Huang, V., Strohbach, M.: A Resource Model for the Real World Internet. In: Lukowicz, P., Kunze, K., Kortuem, G. (eds.) EuroSSC 2010. LNCS, vol. 6446, pp. 163–176. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  3. 3.
    Haroon, M., Handte, M., Marrón, P.: Generic role assignment: a uniform middleware abstraction for configuration of pervasive systems. In: Proc. of the Pervasive Computing and Communications (PerCom’s 2009), Galveston, United States, pp. 1–6 (2009)Google Scholar
  4. 4.
    Payam, B.: D3.6 Final SENSEI Architecture Framework, Public SENSEI Deliverable. CEA-LETI (2011)Google Scholar
  5. 5.
    De, S., Barnaghi, P., Bauer, M., Meissner, S.: Service modeling for the Internet of Things, pp. 949–955 (2011)Google Scholar
  6. 6.
    Semantic Sensor Network XG Final Report, http://www.w3.org/2005/Incubator/ssn/XGR-ssn-20110628/
  7. 7.
    Henson, C., Thirunarayan, K., Sheth, A., Hitzler, P.: Representation of Parsimonious Covering Theory in OWL-DL. In: Proc. of the 8th International Workshop on OWL: Experiences and Directions (OWLED 2011), San Francisco, CA, United States (2011)Google Scholar
  8. 8.
    Thirunarayan, K., Henson, C.A., Sheth, A.P.: Situation awareness via abductive reasoning from semantic sensor data: a preliminary report. In: Proc. of the International Symposium on Collaborative Technologies and Systems (CTS 2009), Balitimore, Maryland, USA, pp. 111–118 (2009)Google Scholar
  9. 9.
    Henson, C., Sheth, A., Thirunararyan, K.: Semantic Perception: A Semantic Approach to Convert Sensory Observations to Abstractions. In: Proc. of the IEEE Internet Computing (2012)Google Scholar
  10. 10.
    Bizer, C., Heath, T., Berners-Lee, T.: Linked data-the story so far. International Journal on Semantic Web and Information Systems (IJSWIS) 5(3), 1–22 (2009)CrossRefGoogle Scholar
  11. 11.
    Henson, C.A., Pschorr, J.K., Sheth, A.P., Thirunarayan, K.: SemSOS: Semantic sensor observation service. In: Proc. of the International Symposium on Collaborative Technologies and Systems (CTS 2009), Balitimore, Maryland, USA, pp. 44–53 (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Shuai Zhao
    • 1
  • Yang Zhang
    • 1
  • Junliang Chen
    • 1
  1. 1.State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijingChina

Personalised recommendations