A Threshold Autoregressive Model for Software Aging

Long running software systems such as client-server type systems are known to experience a kind of aging phenomenon called software aging, one in which the accumulation of errors during the execution of software leads to performance degradation and eventually results in failure. To study and counteract the phenomenon of software aging, we collect and log data on several system resource usage and activity parameters of a Web server. Based on the experimental results, we argue that software aging process could be divided into four stages: robust stage, transition stage, failure-probable stage and failure stage. A non-linear threshold autoregressive (TAR) model is then proposed to model and forecast the resource usage in these stages. In comparison with AR model, TAR model is more accurate