Enhancing intelligence and dependability of a product line enabled pervasive middleware

  • Authors:

  • Weishan Zhang;Klaus Marius Hansen;Thomas Kunz

  • Affiliations:

  • Computer Science Department, University of Aarhus, Aabogade 34, 8200 Aarhus N, Denmark;University of Iceland, Sæmundurgata 2, 101 Reykjavík, Iceland and University of Aarhus, Aabogade 34, 8200 Aarhus N, Denmark;Department of Systems and Computer Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, Canada K1S 5B6

  • Venue:
  • Pervasive and Mobile Computing
  • Year:
  • 2010

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Abstract

To provide good support for user-centered application scenarios in pervasive computing environments, pervasive middleware must react to context changes and prepare services accordingly. At the same time, pervasive middleware should provide extended dependability via self-management capabilities, to conduct self-diagnosis of possible malfunctions using the current runtime context, and self-configuration and self-adaptation when there are service mismatches. In this article, we present an approach to combine the power of BDI practical reasoning and OWL/SWRL ontologies theoretical reasoning in order to improve the intelligence of pervasive middleware, supported by a set of Self-Management Pervasive Service (SeMaPS) ontologies featuring dynamic context, complex context, and self-management rules modeling. In this approach, belief sets are enriched with the results of OWL/SWRL theoretical reasoning to derive beliefs that cannot be obtained directly or explicitly. This is demonstrated with agents negotiating sports appointments. To cope with self-management, the corresponding monitoring, configuration, adaptation and diagnosis rules are developed based on OWL and SWRL utilizing SeMaPS ontologies. Evaluations show this combined reasoning approach can perform well, and that Semantic Web-based self-management is promising for pervasive computing environments.