A Practice of Forecasting Software Aging in an IIS Web Server Using SVM

Software aging is a phenomenon observed in a long running software application, where the state of software degrades and leads to performance degradation, hang/crash failures or both. In fact, it is difficult to detect software aging due to the long delay before aging appearance. Therefore, how to fast and accurately detect software aging problem in a long running system is a big challenge. Since software aging has been studied two decades, many scholars focused on Markov model or time series to model software aging process, however, classification algorithm as a power method has been neglected. In this paper, a classification algorithm called support vector machine is used to model software aging process through collected parameters of an IIS web server that is a running commercial server. Through the analysis of the experiment results, using SVM for software aging prediction is an efficient way to predict software aging in advance.