Modelling user preferences and configuring services in B3G devices

Demestichas, KP; Koutsorodi, AA; Adamopoulou, EF; Theologou, ME

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