A comparative study of hybrid, time-based, and condition-based rejuvenation policies

Software aging, caused by the accumulation of errors and depletion of system resources, degrades the performance of long-running software systems and increases their failure risk. Software rejuvenation alleviates this effect by periodically restoring the system state, and existing rejuvenation strategies are commonly classified as time-based or condition-based. Time-based rejuvenation is easy to implement but lacks adaptability to evolving degradation, whereas condition-based rejuvenation improves efficiency at the expense of frequent inspections and increased operational cost. To overcome these limitations, this paper proposes a hybrid rejuvenation policy that combines scheduled rejuvenation with state-dependent inspections. Under a unified Markovian aging–failure–repair model, we analytically evaluate time-based, condition-based, and hybrid rejuvenation policies using a common stochastic framework. Closed-form expressions for steady-state availability, user-perceived availability, and expected operational cost are derived. Numerical experiments demonstrate that the hybrid policy achieves a more favorable availability–cost tradeoff by retaining the simplicity of time-based rejuvenation while incorporating the adaptive features of condition-based control.