In pervasive environments, Body Area Networks (BANs) are characterized by the mobility of their users. BANs can continuously interact with each other, thus enabling the provision of new applications and services at runtime. New complex services can be provided by composing simpler services 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 possible 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 network mobility and intermittent connectivity, our approach is to cluster nodes in the sensor network based on their connectivity 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 implementation of our architecture, by the study of the statistical model of complex services, and by experimental evaluations.

Service discovery and composition in body area networks

RIBONI, DANIELE
2011

Abstract

In pervasive environments, Body Area Networks (BANs) are characterized by the mobility of their users. BANs can continuously interact with each other, thus enabling the provision of new applications and services at runtime. New complex services can be provided by composing simpler services 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 possible 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 network mobility and intermittent connectivity, our approach is to cluster nodes in the sensor network based on their connectivity 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 implementation of our architecture, by the study of the statistical model of complex services, and by experimental evaluations.
9789639799172
Computer science applications; Computer vision and pattern recognition; Computer networks and communications; Artificial intelligence
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11584/197419
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