Time-Cognizant Recovery Processing for Embedded Real-Time Databases

Recovery processing in embedded real-time databases (ERTDBs) is more complex than traditional databases. In this paper, the classifications and consistency constraints of data and transactions in embedded real-time databases are given first. Then time-cognizant recovery principles for different classes of data and transactions are discussed. In terms of these principles, a time-cognizant recovery scheme based on real-time logging is presented, which is suitable for a class of embedded real-time databases applications. Performance evaluations show that the suggested scheme has better performances than traditional recovery techniques in two aspects: the missing deadlines percent of transactions and the time of system denying services after crashes.

[1]  Sang Hyuk Son,et al.  Achieving bounded and predictable recovery using real-time logging , 2002, Proceedings. Eighth IEEE Real-Time and Embedded Technology and Applications Symposium.

[2]  Tei-Wei Kuo,et al.  Shadowing-based crash recovery schemes for real-time database systems , 1999, Proceedings of 11th Euromicro Conference on Real-Time Systems. Euromicro RTS'99.

[3]  Krithi Ramamritham,et al.  System Failure and Recovery , 2001, Real-Time Database Systems.

[4]  Azer Bestavros.  Advances in Real-Time Database Systems Research: Special Section on RTDBS of ACM SIGMOD Record 25(1), March 1996. , 1996 .

[5]  Wan Choi,et al.  No-log recovery mechanism using stable memory for real-time main memory database systems , 1999, Proceedings Sixth International Conference on Real-Time Computing Systems and Applications. RTCSA'99 (Cat. No.PR00306).

[6]  Donald F. Towsley,et al.  Data Placement, Logging and Recovery in Real-Time Active Databases , 1995, ARTDB.

[7]  Jing Huang,et al.  Impact of timing constraints on real-time database recovery , 1996, CIKM '96.

[8]  Jayant R. Haritsa,et al.  Real-Time Database Systems in the New Millenium , 2004, Real-Time Systems.

[9]  John McPherson,et al.  Implementing Atomicity in Two Systems: Techniques, Tradeoffs, and Experience , 1993, IEEE Trans. Software Eng..

[10]  Sixto Ortiz.  Embedded Databases Come out of Hiding , 2000, Computer.

[11]  Michael A. Olson,et al.  Selecting and Implementing an Embedded Database System , 2000, Computer.

[12]  Azer Bestavros.  Advances in real-time database systems research , 1996, SGMD.

[13]  Hamid Pirahesh,et al.  ARIES: a transaction recovery method supporting fine-granularity locking and partial rollbacks using write-ahead logging , 1998 .