Mining software aging: A neural network approach

This paper investigates the use of artificial neural networks (ANN) to predict software aging phenomenon. We analyze resource usage data collected on a typical long-running software system: a Web server. A multi-layer perceptron feed forward artificial neural network was trained on an Apache Web server dataset to predict future server resource exhaustion through univariate time series forecasting. The results were benchmarked against those obtained from non-parametric statistical techniques, parametric time series models and empirical modeling techniques reported in the literature.