Availability Modeling and Analysis for Data Backup and Restore Operations

Data backup operation is an essential part of common IT system administration to protect against data loss caused by any storage failures, human errors, or disasters. Lost data can be recovered from the backed up data if it exists. Since the backup and restore operations accrue downtime overhead or performance degradation, they have to be designed to ensure the data reliability while minimizing the performance and availability overhead. In this paper, we study the impacts of different backup policies on availability measures such as storage availability, system availability, and user-perceived availability. Backup and restore operations are designed using SysML Activity diagrams that are automatically translated into Stochastic Reward Net (SRN) to compute the availability measures. Our numerical results show the effectiveness of the combination of full backup and partial backup in terms of user-perceived data availability and data loss rate. Furthermore, the sensitivity ranking can help improve the availability measures.