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Reactive vs. Proactive Detection of Quality of Service Problems

This paper summarizes our earlier contributions on reactive and proactive detection of quality of service problems. The first contribution is applying statistical control charts to reactively detect QoS violations. The second contribution is applying …

An automated approach to forecasting QoS attributes based on linear and non-linear time series modeling

Predicting future values of Quality of Service (QoS) attributes can assist in the control of software intensive systems by preventing QoS violations before they happen. Currently, many approaches prefer Autoregressive Integrated Moving Average …

An approach to forecasting QoS attributes of web services based on ARIMA and GARCH models

Availability of several web services having a similar functionality has led to using quality of service (QoS) attributes to support services selection and management. To improve these operations and be performed proactively, time series ARIMA models …

Robust archeopterix: Architecture optimization of embedded systems under uncertainty

Design of embedded systems involves a number of architecture decisions which have a significant impact on its quality. Due to the complexity of today's systems and the large design options that need to be considered, making these decisions is beyond …

Statistical detection of QoS violations based on CUSUM control charts

Currently software systems operate in highly dynamic contexts, and consequently they have to adapt their behavior in response to changes in their contexts or/and requirements. Existing approaches trigger adaptations after detecting violations in …

Using Automated Control Charts for the Runtime Evaluation of QoS Attributes

As modern software systems operate in a highly dynamic context, they have to adapt their behaviour in response to changes in their operational environment or/and requirements. Triggering adaptation depends on detecting quality of service (QoS) …

Gibbs sampling for SARMA models

This paper introduces a fast, easy and accurate Gibbs sampling algorithm to develop a Bayesian inference for a multiplicative seasonal autoregressive moving average (SARMA) model. The proposed algorithm uses values generated from normal and inverse …

Bayesian Inference for Seasonal ARMA Models: A Gibbs Sampling Approach

This paper introduces a fast, easy and accurate Gibbs sampling algorithm to develop a Bayesian inference for a multiplicative seasonal autoregressive moving average (SARMA) model. The proposed algorithm uses values generated from normal and inverse …

Estimating the quantitative values for the monitoring and evaluation indicators of the population problem (2005-2017)

The Ministry of Health and Population, in collaboration with the ministries and agencies concerned with the population problem. Developed a National Strategic Plan 2007-2017, to reach total fertility rate of (2.1 children per woman) by 2017 at the …