Predicting service metrics for cluster-based services using real-time analytics

Predicting the performance of cloud services is intrinsically hard. In this work, we pursue an approach based upon statistical learning, whereby the behaviour of a system is learned from observations. Specifically, our testbed implementation collects device statistics from a server cluster and uses...

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Vydané v:	2015 11th International Conference on Network and Service Management (CNSM) s. 135 - 143
Hlavní autori:	Yanggratoke, Rerngvit, Ahmed, Jawwad, Ardelius, John, Flinta, Christofer, Johnsson, Andreas, Gillblad, Daniel, Stadler, Rolf
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IFIP 01.11.2015
Predmet:	cloud computing Computational modeling machine learning Measurement network analytics Predictive models Quality of service Real-time systems Servers Statistical learning Yttrium
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