A New Software Rejuvenation Model for Android

Android users are sometimes troubled by slow UI responses or even application/OS crashes. These issues are typically caused by software aging, a phenomenon characterized by progressive degradation of performance and functionality observed in long-running software systems. A practical and widely used approach to combat software aging is software rejuvenation, i.e. manual or scheduled restart of an application or a device. To reduce service outages, proactive rejuvenation is preferred, which strives to balance application downtime and performance level. However, traditional rejuvenation models cannot be directly applied to Android applications or system, as they do not address user experience, such as avoiding rejuvenation during high activity phases. In this work we exploit the fact that the usage time of mobile phones is typically fragmented in daily life, with periodic switches between active and sleep modes. We propose proactive rejuvenation strategies, which consider both usage and age factors. In particular, we model the usage behavior and aging process as individual Stochastic Petri-Nets, and then compose them into Continuous Time Markov Chains. We evaluate our models via numerical experiments and demonstrate the effectiveness and advantages of the proposed rejuvenation approach.