By Topic

Design, Implementation, and Evaluation of a Repairable Database Management System

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
T. Chiueh ; Rether Networks Inc., Centereach, NY, USA ; D. Pilania

Although conventional database management systems are designed to tolerate hardware and to a lesser extent even software errors, they cannot protect themselves against syntactically correct and semantically damaging transactions, which could arise because of malicious attacks or honest mistakes. The lack of fast post-intrusion or post-error damage repair in modern DBMSs results in a longer Mean Time to Repair (MTTR) and sometimes permanent data loss that could have been saved by more intelligent repair mechanisms. In this paper, we describe the design and implementation of Phoenix - a system that significantly improves the efficiency and precision of a database damage repair process after an intrusion or operator error and thus, increases the overall database system availability. The two key ideas underlying Phoenix are (1) maintaining persistent inter-transaction dependency information at run time to allow selective undo of database transactions that are considered "infected" by the intrusion or error in question and (2) exploiting information present in standard database logs for fast selective undo. Performance measurements on a fully operational Phoenix prototype, which is based on the PostgreSQL DBMS, demonstrate that Phoenix incurs a response time and a throughput penalty of less than 5% and 8%, respectively, under the TPC-C benchmark, but it can speed up the post-intrusion database repair process by at least an order of magnitude when compared with a manual repair process.

Published in:

21st International Conference on Data Engineering (ICDE'05)

Date of Conference:

05-08 April 2005