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

@article{Amin2012AnAA,
  title={An automated approach to forecasting QoS attributes based on linear and non-linear time series modeling},
  author={Ayman Amin and Lars Grunske and Alan W. Colman},
  journal={2012 Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering},
  year={2012},
  pages={130-139}
}
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 (ARIMA) models for this task, and assume the QoS attributes' behavior can be linearly modeled. However, the analysis of real QoS datasets shows that they are characterized by a highly dynamic and mostly nonlinear behavior to the extent that existing ARIMA… CONTINUE READING
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