Translation of application-level terms to resource-level attributes across the cloud stack layers

Kousiouris, G; Kyriazis, D; Gogouvitis, S; Menychtas, A; Konstanteli, K; Varvarigou, T

dc.contributor.author	Kousiouris, G	en
dc.contributor.author	Kyriazis, D	en
dc.contributor.author	Gogouvitis, S	en
dc.contributor.author	Menychtas, A	en
dc.contributor.author	Konstanteli, K	en
dc.contributor.author	Varvarigou, T	en
dc.date.accessioned	2014-03-01T02:47:30Z
dc.date.available	2014-03-01T02:47:30Z
dc.date.issued	2011	en
dc.identifier.issn	15301346	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/33185
dc.subject	Artificial neural networks	en
dc.subject	Cloud computing	en
dc.subject	performance estimation	en
dc.subject	real-time Clouds	en
dc.subject	SLA translation	en
dc.subject.other	Accurate performance	en
dc.subject.other	Amount of information	en
dc.subject.other	Application scenario	en
dc.subject.other	Black box approach	en
dc.subject.other	Infrastructure services	en
dc.subject.other	Interactivity	en
dc.subject.other	Performance estimation	en
dc.subject.other	real-time Clouds	en
dc.subject.other	SLA translation	en
dc.subject.other	Computer systems	en
dc.subject.other	E-learning	en
dc.subject.other	Estimation	en
dc.subject.other	Neural networks	en
dc.subject.other	User interfaces	en
dc.subject.other	Cloud computing	en
dc.title	Translation of application-level terms to resource-level attributes across the cloud stack layers	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ISCC.2011.5984009	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ISCC.2011.5984009	en
heal.identifier.secondary	5984009	en
heal.publicationDate	2011	en
heal.abstract	The emergence of new environments such as Cloud computing highlighted new challenges in traditional fields like performance estimation. Most of the current cloud environments follow the Software, Platform, Infrastructure service model in order to map discrete roles / providers according to the offering in each ""layer"". However, the limited amount of information passed from one layer to the other has raised the level of difficulty in translating user-understandable application terms from the Software layer to resource specific attributes, which can be used to manage resources in the Platform and Infrastructure layers. In this paper, a generic black box approach, based on Artificial Neural Networks is used in order to perform the aforementioned translation. The efficiency of the approach is presented and validated through different application scenarios (namely FFMPEG encoding and real-time interactive e-Learning) that highlight its applicability even in cases where accurate performance estimation is critical, as in cloud environments aiming to facilitate real-time and interactivity. © 2011 IEEE.	en
heal.journalName	Proceedings - IEEE Symposium on Computers and Communications	en
dc.identifier.doi	10.1109/ISCC.2011.5984009	en
dc.identifier.spage	153	en
dc.identifier.epage	160	en