Shadowing-based crash recovery schemes for real-time database systems

Predictable performance in the event of failures is of paramount importance in most safety critical real-time database systems. Our research addresses new crash recovery techniques that accommodate pre-run-time timing analysis and utilize design-time information about transactions' data access patterns to improve performance at run time and system restart time. The schemes we will propose are based on a form of shadowing. In contrast to the shadow version algorithm as described previously our schemes reduce overheads at run time, shorten the blocking duration necessary in the transactions' atomic commitment stage, eliminate dynamic storage allocation and reclamation, and permit very fast and bounded-time recovery after a crash by simply retrieving the master record and system version directory from nonvolatile storage. The data structures and algorithms used by our recovery schemes differ when different concurrency control protocols are used. We analyze their characteristics and their impacts on the performance of real-time database systems. Quantitative evaluation of our technique indicates the schemes are much more efficient than traditional log-based techniques.