1st International ICST Conference on Bio Inspired Models of Network, Information and Computing Systems

Research Article

Bio-inspired context gathering in loosely coupled computing environments

  • @INPROCEEDINGS{10.1145/1315843.1315862,
        author={Carsten  Jacob and David Linner and Stephan  Steglich and Ilja Radusch},
        title={Bio-inspired context gathering in loosely coupled computing environments},
        proceedings={1st International ICST Conference on Bio Inspired Models of Network, Information and Computing Systems},
        publisher={ACM},
        proceedings_a={BIONETICS},
        year={2006},
        month={12},
        keywords={},
        doi={10.1145/1315843.1315862}
    }
    
  • Carsten Jacob
    David Linner
    Stephan Steglich
    Ilja Radusch
    Year: 2006
    Bio-inspired context gathering in loosely coupled computing environments
    BIONETICS
    ACM
    DOI: 10.1145/1315843.1315862
Carsten Jacob1,*, David Linner2,*, Stephan Steglich2,*, Ilja Radusch2,*
  • 1: Fraunhofer Institute for Open Communication Systems (FOKUS), Kaiserin-August-Allee 31, 10589 Berlin, Germany
  • 2: Technische Universität Berlin, Sekr. FR 5-14, Franklinstrasse 28/29, 10587 Berlin, Germany
*Contact email: carsten.jacob@fokus.fraunhofer.de, david.linner@tu-berlin.de, stephan.steglich@tu-berlin.de, ilja.radusch@tu-berlin.de

Abstract

Context-awareness is a key requirement of human-centric computing systems. Applications may ease user interaction or even anticipate the behavior of the user when utilizing information about the current context. The pervasive provision of context data represents a major challenge in this scope. For that reason we introduce an approach for gathering, disseminating, and interpreting context data in dynamic, highly distributed systems, which are mostly disconnected from central networking infrastructures. On the one hand we describe architectural consideration addressing functional elements and their organization in the computing environment. On the other hand we incorporate a model for request-driven context gathering and a biologically-inspired approach for weighting, storing and forwarding context data. The conceptual considerations are complemented with a description of our first efforts in realizing our approach on top of a peer-to-peer framework.