ACM Transactions on Database Systems (TODS)
Physical integrity in a large segmented database
ACM Transactions on Database Systems (TODS)
A history and evaluation of System R
Communications of the ACM
ACM Transactions on Database Systems (TODS)
Database Management Systems
Transaction Processing: Concepts and Techniques
Transaction Processing: Concepts and Techniques
Implementing Atomicity in Two Systems: Techniques, Tradeoffs, and Experience
IEEE Transactions on Software Engineering
LGeDBMS: a small DBMS for embedded system with flash memory
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
FlashDB: dynamic self-tuning database for NAND flash
Proceedings of the 6th international conference on Information processing in sensor networks
Stasis: flexible transactional storage
OSDI '06 Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7
Power-aware remote replication for enterprise-level disaster recovery systems
ATC'08 USENIX 2008 Annual Technical Conference on Annual Technical Conference
Design and implementation of MLC NAND flash-based DBMS for mobile devices
Journal of Systems and Software
Segment-based recovery: write-ahead logging revisited
Proceedings of the VLDB Endowment
MLC-flash-friendly logging and recovery for databases
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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Nowadays, due to the increased user requirements of the fast and reliable data management operation for mobile applications, major device vendors use embedded DBMS for their mobile devices such as MP3 players, mobile phones, digital cameras and PDAs. However, database logging is the major bottleneck against the fast response time. There has been a lot of work minimizing logging overhead but no single recovery method provides the best performance to a variety of database workloads. In this paper, we present a novel recovery method called adaptive logging which can switch the logging method from ARIES to shadow paging adaptively at a page level according to the update state of each page on run time. Also, we propose a log compaction method called deferred logging which removes redundant logs by deferring to create log records until the updated data page is flushed or until the transaction commits. Deferred logging is coupled with adaptive logging seamlessly so that it boosts the performance of adaptive logging by reducing the typical overhead of hybrid methods. We have implemented the proposed approaches to our embedded DBMS which was deployed to more than 10 million mobile devices and evaluated them through a real world application on a mobile device. The result shows that our approaches can reduce logging overhead significantly and consequently can improve the response time of both small update transaction and large update transaction effectively.