Modeling and Performance Analysis of Software Rejuvenation Policies for Multiple Degradation Systems

Software rejuvenation is a preventive and proactive technology to counteract the phenomenon of software aging and system failures and to improve the system reliability. In this paper we present and analyze three software rejuvenation policies for an operational software system with multiple degradations, called preemptive rejuvenation, delayed rejuvenation and mixed rejuvenation. These policies consider both history data and current running state, and the rejuvenation action is triggered on the basis of predetermined performance threshold and rejuvenation interval respectively. Continuous-time Markov chains are used to describe the analytic models. To evaluate these polices expediently, we utilize deterministic and stochastic Petri nets to solve the models. Numerical results show that the deployment of software rejuvenation in the system leads to significant improvement in availability and throughput. These three rejuvenation policies are better than the standard rejuvenation policy, and the mixed policy is the best one.