An application of case-based reasoning to the adaptive management of wireless networks

Barbera, M; Barbero, C; Dal Zovo, P; Farinaccio, F; Gkroustiotis, E; Kyriazakos, S; Mura, I; Previti, G

dc.contributor.author	Barbera, M	en
dc.contributor.author	Barbero, C	en
dc.contributor.author	Dal Zovo, P	en
dc.contributor.author	Farinaccio, F	en
dc.contributor.author	Gkroustiotis, E	en
dc.contributor.author	Kyriazakos, S	en
dc.contributor.author	Mura, I	en
dc.contributor.author	Previti, G	en
dc.date.accessioned	2014-03-01T01:17:26Z
dc.date.available	2014-03-01T01:17:26Z
dc.date.issued	2002	en
dc.identifier.issn	0302-9743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/14534
dc.subject	Adaptive Management	en
dc.subject	Automated Reasoning	en
dc.subject	Case Base Reasoning	en
dc.subject	Mobile Communication	en
dc.subject	Wireless Network	en
dc.subject	On The Fly	en
dc.subject	Real Time	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.title	An application of case-based reasoning to the adaptive management of wireless networks	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/3-540-46119-1_36	en
heal.identifier.secondary	http://dx.doi.org/10.1007/3-540-46119-1_36	en
heal.language	English	en
heal.publicationDate	2002	en
heal.abstract	This paper describes an innovative application of Case-Based Reasoning methodologies for the dynamic management of wireless telecommunications systems. In spite of the very dynamic nature of mobile communications, wireless networks only possess limited adaptive management capabilities, which are unable to adequately follow traffic fluctuations through flexible and real-time resource assignment reconfigurations. The study described in this paper is an attempt to improve over these limitations, by allowing wireless networks to alleviate the effects of traffic overloads through an automated reasoning about its performance levels and an on-the-fly reconfiguration of resources assignment. The proposed Case-Based Reasoning approach provides a suitable framework to define a simple and scalable solution that easily incorporates the preferences of the network operators.	en
heal.publisher	SPRINGER-VERLAG BERLIN	en
heal.journalName	ADVANCES IN CASE-BASED REASONING	en
heal.bookName	LECTURE NOTES IN ARTIFICIAL INTELLIGENCE	en
dc.identifier.doi	10.1007/3-540-46119-1_36	en
dc.identifier.isi	ISI:000187007600036	en
dc.identifier.volume	2416	en
dc.identifier.spage	490	en
dc.identifier.epage	504	en