3rd International ICST Conference on Body Area Networks

Research Article

Service Discovery and Composition in Body Area Networks

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  • @INPROCEEDINGS{10.4108/ICST.BODYNETS2008.2951,
        author={Matteo Coloberti and Clemens Lombriser and Daniel Roggen and Gerhard  Tr\o{}ster and Renata Guarneri and Daniele Riboni},
        title={Service Discovery and Composition in Body Area Networks},
        proceedings={3rd International ICST Conference on Body Area Networks},
  • Matteo Coloberti
    Clemens Lombriser
    Daniel Roggen
    Gerhard Tröster
    Renata Guarneri
    Daniele Riboni
    Year: 2010
    Service Discovery and Composition in Body Area Networks
    DOI: 10.4108/ICST.BODYNETS2008.2951
Matteo Coloberti1,2,*, Clemens Lombriser3,*, Daniel Roggen3,*, Gerhard Tröster3,*, Renata Guarneri2,*, Daniele Riboni1,*
  • 1: D.I.Co.- University of Milan, Milan, Italy
  • 2: Nokia Siemens Network, Milan, Italy
  • 3: Wearable Computing Lab, ETH Zürich, Switzerland
*Contact email: coloberti@dico.unimi.it, lombriser@ife.ee.ethz.ch, droggen@ife.ee.ethz.ch, troester@ife.ee.ethz.ch, maria.guarneri@nsn.com, riboni@dico.unimi.it


In pervasive environments, Body Area Networks (BANs) are characterized by the mobility of their users. BANs can con- tinuously interact with each other, thus enabling the pro- vision of new applications and services at runtime. New complex services can be provided by composing simpler ser- vices available on neighbouring network nodes. However, since the topology of BANs is continuously changing due to users’ movements, it is unfeasible to specify a-priori all pos- sible configurations under which a given complex service can be composed. In order to address this issue, we introduce a two–layered service discovery and composition architecture, that proactively notifies a distributed service directory with changes in service availability. In order to cope with the net- work mobility and intermittent connectivity, our approach is to cluster nodes in the sensor network based on their con- nectivity patterns. We use a multi–agent state machine to recognize the availability of complex services and to provide them. Our solution is validated by a prototype implementa- tion of our architecture, by the study of the statistical model of complex services, and by experimental evaluations.