A semantic solution for data integration in mixed sensor networks

  • Authors:

  • Ismail Khalil Ibrahim;Reinhard Kronsteiner;Gabriele Kotsis

  • Affiliations:

  • Telecooperation Department, Johannes Kepler University Linz, Altenberger Str. 69, A-4040 Linz, Austria;Telecooperation Department, Johannes Kepler University Linz, Altenberger Str. 69, A-4040 Linz, Austria;Telecooperation Department, Johannes Kepler University Linz, Altenberger Str. 69, A-4040 Linz, Austria

  • Venue:
  • Computer Communications
  • Year:
  • 2005

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Abstract

The number of sensor networks deployed for a manifold of applications is expected to increase dramatically in the coming few years. Advances in wireless communications and the growing interest in wireless networks are spurring this. This growth will not only simplify the access to sensor information but will also motivate the creation of numerous new information. Paradoxically, this growth will make the task of getting meaningful information from disparate sensor nodes not a trivial one. On the one hand, traffic overheads and the increased probabilities of hardware failures make it very difficult to maintain an always-on, ubiquitous service. On the other hand, the heterogeneity of the sensor nodes makes finding, extracting, and aggregating data at the processing elements and sink nodes much harder. These two issues (in addition to course to the distribution, dynamicity, accuracy, and reliability issues) impose the need for more efficient and reliable techniques for information integration of data collected from sensor nodes. In this paper, we first address the issues related to data integration in wireless sensor networks with respect to heterogeneity, dynamicity, and distribution at both the technology and application levels. Second, we present and discuss a query processing algorithm which make use of the semantic knowledge about sensor networks expressed in the form of integrity constraints to reduce network traffic overheads, improve scalability and extensibility of wireless networks and increase the stability and reliability of networks against hardware and software failures. Third, we discuss a uniform interface to data collected from sensor nodes that will map sensor-specific data to the global information source based on a context exported by the data integration system.