Knowledge-base representation and reasoning for the autonomic management of pervasive healthcare

  • Authors:
  • Eleftheria Katsiri

  • Affiliations:
  • Birkbeck, University of London, Malet Street, London WC1E 7HX, Email: eli@dcs.bbk.ac.uk

  • Venue:
  • Proceedings of the 2008 conference on Knowledge-Based Software Engineering: Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering
  • Year:
  • 2008

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Abstract

Two recent programming paradigms, Body Area Networks (BAN) and Body Sensor Networks (BSNs) interact with a ubiquitous computing environment in order to monitor the health and well being of patients in hospitals or at home. Previous work in DSE, Imperial College, discusses the Self Managed Cell (SMC), as the basic architectural pattern of self-configuring and self-managing BAN networks. Devices in BANs become autonomic, by specifying their behavior reactively, in terms of the Ponder2 policy language. As a result, such networks require very little or no user input in order to adapt autonomously to changes in the users' environment, resulting from user activity, device failure, and the addition or loss of services. Body Sensor Networks (BSN) are the next generation pervasive monitoring systems and are significantly lower-scale than BANs. BSN consist of very small nodes with limited computational memory and power resources that are not currently programmable in a reactive (rule-based) manner. This means that the SMC model cannot be applied directly to Body Sensor Networks; a new knowledge representation and reasoning model is needed to program such devices. This paper discusses the design decisions we took the design and implementation of an embedded policy interpreter (EPI) for autonomous BSN nodes.