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Server Availability (SA) is an important measure of overall systems security.Important security systems rely on the availability of their hosting servers todeliver critical security services. Many of these servers offer managementinterface through web mainly using an Apache server. This paper investigatesthe increase of Server Availability by the use of Artificial Neural Networks(ANN) to predict software aging phenomenon. Several resource usage data iscollected and analyzed on a typical long-running software system (a webserver). A Multi-Layer Perceptron feed forward Artificial Neural Network wastrained on an Apache web server data-set to predict future server resourceexhaustion through uni-variate time series forecasting. The results werebenchmarked against those obtained from non-parametric statistical techniques,parametric time series models and empirical modeling techniques reported in theliterature.

Increasing Server Availability for Overall System Security: A Preventive Maintenance Approach Based on Failure Prediction