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...

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Main Authors: C. Mannweiler, A. Klein, J. Schneider, H. D. Schotten
Format: Article
Language:deu
Published: Copernicus Publications 2011-08-01
Series:Advances in Radio Science
Online Access:http://www.adv-radio-sci.net/9/187/2011/ars-9-187-2011.pdf
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spelling doaj-0bd7ff878b294f29a0299886b189798d2020-11-24T23:53:18ZdeuCopernicus PublicationsAdvances in Radio Science 1684-99651684-99732011-08-01918719310.5194/ars-9-187-2011Context-based user grouping for multi-casting in heterogeneous radio networksC. Mannweiler0A. Klein1J. Schneider2H. D. Schotten3Chair for Wireless Communications and Navigation, University of Kaiserslautern, GermanyChair for Wireless Communications and Navigation, University of Kaiserslautern, GermanyChair for Wireless Communications and Navigation, University of Kaiserslautern, GermanyChair for Wireless Communications and Navigation, University of Kaiserslautern, GermanyAlong 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.http://www.adv-radio-sci.net/9/187/2011/ars-9-187-2011.pdf
collection DOAJ
language deu
format Article
sources DOAJ
author C. Mannweiler
A. Klein
J. Schneider
H. D. Schotten
spellingShingle C. Mannweiler
A. Klein
J. Schneider
H. D. Schotten
Context-based user grouping for multi-casting in heterogeneous radio networks
Advances in Radio Science
author_facet C. Mannweiler
A. Klein
J. Schneider
H. D. Schotten
author_sort C. Mannweiler
title Context-based user grouping for multi-casting in heterogeneous radio networks
title_short Context-based user grouping for multi-casting in heterogeneous radio networks
title_full Context-based user grouping for multi-casting in heterogeneous radio networks
title_fullStr Context-based user grouping for multi-casting in heterogeneous radio networks
title_full_unstemmed Context-based user grouping for multi-casting in heterogeneous radio networks
title_sort context-based user grouping for multi-casting in heterogeneous radio networks
publisher Copernicus Publications
series Advances in Radio Science
issn 1684-9965
1684-9973
publishDate 2011-08-01
description 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.
url http://www.adv-radio-sci.net/9/187/2011/ars-9-187-2011.pdf
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