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Modelling user preferences and configuring services in B3G devices

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dc.contributor.author Demestichas, KP en
dc.contributor.author Koutsorodi, AA en
dc.contributor.author Adamopoulou, EF en
dc.contributor.author Theologou, ME en
dc.date.accessioned 2014-03-01T01:28:47Z
dc.date.available 2014-03-01T01:28:47Z
dc.date.issued 2008 en
dc.identifier.issn 1022-0038 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/18971
dc.subject Access selection en
dc.subject Bayesian networks en
dc.subject Heterogeneous networks en
dc.subject Preference modelling en
dc.subject User profiling en
dc.subject.classification Computer Science, Information Systems en
dc.subject.classification Engineering, Electrical & Electronic en
dc.subject.classification Telecommunications en
dc.subject.other Bayesian networks en
dc.subject.other Computer architecture en
dc.subject.other Inference engines en
dc.subject.other Learning algorithms en
dc.subject.other Access network (Anet) en
dc.subject.other access selection en
dc.subject.other Bayesian en
dc.subject.other Business media en
dc.subject.other Greedy algorithms en
dc.subject.other Heterogeneous environments en
dc.subject.other management architectures en
dc.subject.other Optimal allocation en
dc.subject.other Quality levels en
dc.subject.other simulation results en
dc.subject.other Springer (CO) en
dc.subject.other Usage context en
dc.subject.other Usage patterns en
dc.subject.other User preferences en
dc.subject.other Network architecture en
dc.title Modelling user preferences and configuring services in B3G devices en
heal.type journalArticle en
heal.identifier.primary 10.1007/s11276-007-0044-7 en
heal.identifier.secondary http://dx.doi.org/10.1007/s11276-007-0044-7 en
heal.language English en
heal.publicationDate 2008 en
heal.abstract This paper discusses a management architecture for devices operating in heterogeneous environments, that enables access network selection through terminal-controlled, preference-based mechanisms. In this domain two problems are identified, mathematically formulated and solved: Intelligent Access Selection (IAS) and Modelling and Adaptation to User Preferences (MAUP). Their objective is to compute the optimal allocation of services to access networks and quality levels, and to dynamically determine user preferences according to the usage context, respectively. A greedy algorithm is proposed for the IAS problem, while the MAUP problem is handled through the construction of a Bayesian network that allows inference and learning of profile and usage patterns. Extensive simulation results of the proposed methods and algorithms are also presented. © 2007 Springer Science+Business Media, LLC. en
heal.publisher SPRINGER en
heal.journalName Wireless Networks en
dc.identifier.doi 10.1007/s11276-007-0044-7 en
dc.identifier.isi ISI:000257394500011 en
dc.identifier.volume 14 en
dc.identifier.issue 5 en
dc.identifier.spage 699 en
dc.identifier.epage 713 en


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