Self-organized data ecologies for pervasive situation-aware services: the knowledge networks approach

  • Authors:
  • Nicola Bicocchi;Matthias Baumgarten;Nermin Brgulja;Rico Kusber;Marco Mamei;Maurice Mulvenna;Franco Zambonelli

  • Affiliations:
  • Dipartimento di Scienze e Metodi dell'Ingegneria, Università di Modena e Reggio Emilia, Reggio Emilia, Italy;School of Computing and Mathematics, University of Ulster, Belfast, UK;ComTec, University of Kassel, Kassel, Germany;ComTec, University of Kassel, Kassel, Germany;Dipartimento di Scienze e Metodi dell'Ingegneria, Università di Modena e Reggio Emilia, Reggio Emilia, Italy;School of Computing and Mathematics, University of Ulster, Belfast, UK;Dipartimento di Scienze e Metodi dell'Ingegneria, Università di Modena e Reggio Emilia, Reggio Emilia, Italy

  • Venue:
  • IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
  • Year:
  • 2010

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Abstract

Pervasive computing services exploit information about the physical world both to adapt their own behavior in a context-aware way and to deliver to users enhanced means of interaction with their surrounding environment. The technology to acquire digital information about the physical world is becoming more available, making services at risk of being overwhelmed by such growing amounts of data. This calls for novel approaches to represent and automatically organize, aggregate, and prune such data before delivering them to services. In particular, individual data items should form a sort of self-organized ecology in which, by linking and combining with each other into sorts of "knowledge networks" (KNs), they are able to provide compact and easy-tobe-managed higher level knowledge about situations occurring in the environment. In this context, the contribution of this paper is twofold. First, with the help of a simple case study, we motivate the need to evolve from models of "context awareness" toward models of "situation awareness" via proper self-organized "KN" tools, and we introduce a general reference architecture for KNs. Second, we describe the design and implementation of a KN toolkit that we have developed, and we exemplify and evaluate algorithms for knowledge self-organization integrated within it. Open issues and future research directions are also discussed.