Context-based user grouping for multi-casting in heterogeneous radio networks
Along with the rise of sophisticated smartphones and smart spaces, the availability of both static and dynamic context information has steadily been increasing in recent years. Due to the popularity of social networks, these data are complemented by profile information about individual users. Making...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | deu |
| Published: |
Copernicus Publications
2011-08-01
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| Series: | Advances in Radio Science |
| Online Access: | http://www.adv-radio-sci.net/9/187/2011/ars-9-187-2011.pdf |
| Summary: | Along with the rise of sophisticated smartphones and smart spaces, the
availability of both static and dynamic context information has steadily been
increasing in recent years. Due to the popularity of social networks, these
data are complemented by profile information about individual users. Making
use of this information by classifying users in wireless networks enables
targeted content and advertisement delivery as well as optimizing network
resources, in particular bandwidth utilization, by facilitating group-based
multi-casting. In this paper, we present the design and implementation of a
web service for advanced user classification based on user, network, and
environmental context information. The service employs simple and advanced
clustering algorithms for forming classes of users. Available service
functionalities include group formation, context-aware adaptation, and
deletion as well as the exposure of group characteristics. Moreover, the
results of a performance evaluation, where the service has been integrated in
a simulator modeling user behavior in heterogeneous wireless systems, are
presented. |
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| ISSN: | 1684-9965 1684-9973 |