Ricardo Ehlers

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In a cloud computing environment, companies have the ability to allocate resources according to demand. However, there is a delay that may take minutes between the request for a new resource and it being ready for using. This causes the reactive techniques, which request a new resource only when the system reaches a certain load threshold, to be not(More)
In a cloud computing environment, companies can allocate and de-allocate computing resources according to demand. However, this task does not happen instantaneously. There is a delay, which may take minutes, between the request for a new resource and it be ready for use. To resolve this problem we need forecast the future demand for then allocate the(More)
Improve resource provisioning for applications hosted in the cloud is a major research challenge. This is because is necessary to address two conflicting objectives: meet customer requirements; and save money. As there is a delay, which can take minutes, between the request for a new resource and it be ready for use, it is necessary to predict the future(More)
In this paper we assess Bayesian estimation and prediction using integrated Laplace approximation (INLA) on a stochastic volatility model. This was performed through a Monte Carlo study with 1000 simulated time series. To evaluate the estimation method, two criteria were considered: the bias and square root of the mean square error (smse). The criteria used(More)
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