A service‐agnostic method for predicting service metrics in real time

Summary We predict performance metrics of cloud services using statistical learning, whereby the behaviour of a system is learned from observations. Specifically, we collect device and network statistics from a cloud testbed and apply regression methods to predict, in real‐time, client‐side service...

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Vydáno v:	International journal of network management Ročník 28; číslo 2
Hlavní autoři:	Yanggratoke, Rerngvit, Ahmed, Jawwad, Ardelius, John, Flinta, Christofer, Johnsson, Andreas, Gillblad, Daniel, Stadler, Rolf
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Chichester Wiley Subscription Services, Inc 01.03.2018
Témata:	Accuracy Cloud computing Design and implementations Distance learning Distributed computer systems Forecasting Learning systems machine learning Mean absolute error Network statistics Operating systems Performance measurement Performance metrics Prediction accuracy Predictions quality of service Real time Real time network Real-time analytics real-time network analytics Regression analysis Statistical analysis statistical learning Statistics Testbeds Video streaming Video transmission
ISSN:	1055-7148, 1099-1190, 1099-1190
On-line přístup:	Získat plný text
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