An approach for identifying failure-prone state of computer system

Controlled experiment can help us to better understand the root origin and evolution of software aging. Detection and/or quantification of software aging is an important research issue. The experimental observations may be obscure, although it may implicate much useful information. In this paper, we first report the memory thrashing phenomenon observed in our controlled experiment, and find the vibration frequency of available memory may be a potential indicator of aging. We then characterize and measure the vibration frequency by using amplitude spectrum analysis. Accordingly, a metric is proposed to measure the aging extent implicated in the vibration frequency by using power spectrum analysis. Finally, we propose an approach for online aging detection based on sliding window Fourier transform. The metric is calculated for each “window” to evaluate the severity of aging at a given time instant.