A management scheme for distributed cross-layer reconfigurations in the context of cognitive B3G infrastructures

Dimitrakopoulos, G; Tsagkaris, K; Demestichas, K; Adamopoulou, E; Demestichas, P

dc.contributor.author	Dimitrakopoulos, G	en
dc.contributor.author	Tsagkaris, K	en
dc.contributor.author	Demestichas, K	en
dc.contributor.author	Adamopoulou, E	en
dc.contributor.author	Demestichas, P	en
dc.date.accessioned	2014-03-01T01:25:41Z
dc.date.available	2014-03-01T01:25:41Z
dc.date.issued	2007	en
dc.identifier.issn	0140-3664	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17727
dc.subject	Autonomic computing	en
dc.subject	B3G wireless infrastructures	en
dc.subject	Bayesian networks	en
dc.subject	Cognitive networks	en
dc.subject	Cross-layer optimization	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.classification	Telecommunications	en
dc.subject.other	Algorithms	en
dc.subject.other	Bayesian networks	en
dc.subject.other	Distributed computer systems	en
dc.subject.other	Management science	en
dc.subject.other	Mobile computing	en
dc.subject.other	Network protocols	en
dc.subject.other	Autonomic computing	en
dc.subject.other	B3G wireless infrastructures	en
dc.subject.other	Cognitive networks	en
dc.subject.other	Cross-layer optimization	en
dc.subject.other	Cognitive systems	en
dc.title	A management scheme for distributed cross-layer reconfigurations in the context of cognitive B3G infrastructures	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.comcom.2007.09.011	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.comcom.2007.09.011	en
heal.language	English	en
heal.publicationDate	2007	en
heal.abstract	Current research efforts in wireless communications are targeted at the evolution of B3G (Beyond the 3rd Generation) wireless infrastructures. The operation of B3G infrastructures envisions dynamic adaptations to external stimuli, which can be facilitated through the exploitation of cognitive networking potentials. Cognitive networks dispose mechanisms for dynamically selecting their configuration (algorithms and parameter values, at different layers of the protocol stack), through appropriate management functionality that takes into account the context of operation (environment characteristics and requirements), profiles, goals, policies and knowledge that derives from previous experience. This paper focuses on such management functionality and it addresses a problem, dealing with ""Distributed, Cross-Layer Reconfigurations"" (DCLR), which aims at assessing and selecting the most appropriate configuration per network element in a cognitive network. In essence, this work contributes in four main areas. First, a fully distributed formulation and solution to the DCLR problem is provided, which is important for the management of a particular reconfigurable element in a cognitive context. Second, robust learning and adaptation, strategies are proposed, for estimating and gaining knowledge of the performance potentials of alternate reconfigurations. Third, a computationally efficient solution to the problem of exploiting the performance potentials of reconfigurations is provided, in order to rate reconfigurations and finally select the best ones. Finally, results that expose the behaviour and efficiency of the proposed schemes, are presented. © 2007 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	Computer Communications	en
dc.identifier.doi	10.1016/j.comcom.2007.09.011	en
dc.identifier.isi	ISI:000252533700031	en
dc.identifier.volume	30	en
dc.identifier.issue	18	en
dc.identifier.spage	3807	en
dc.identifier.epage	3822	en