Efficient Analysis of Repairable Computing Systems Subject to Scheduled Checkpointing

To improve the success probability of a mission execution, scheduled checkpointing is often implemented to save completed portions of the mission task so that a system can resume the mission execution effectively after its restoration whenever the system failure occurs. This paper considers a repairable computing system subject to the scheduled checkpointing. The checkpointing intervals are deterministic, but can be even or uneven. The system repair time is fixed while the system time-to-failure can follow any arbitrary type of distributions. The maximum number of repairs is specified by a certain threshold value. A multi-valued decision diagram (MDD)-based analytical approach is proposed to evaluate the exact success probability of a mission execution for the considered repairable system. The proposed approach enables generating a compact mission MDD model where identical subMDD models can be merged to improve computational efficiency and reduce storage requirement. The MDD model, once being constructed, can be reused for system reliability evaluations using different input parameter values. A benchmark study is presented to show the efficiency of proposed MDD approach. A case study is performed to illustrate the application of the proposed MDD approach to facilitate decision making about proper system design and parameter selection.