Towards Model-based Management of Database Fragmentation

The performance of a database can significantly deteriorate due to the fragmentation of data/index files. Manual database defragmentation and performance optimization remain time consuming and even infeasible as it requires knowledge of the complicated behavior of fragmentation and its relationships with system parameters. We propose a model-based detection and management framework for the database fragmentation which can automatically optimize database performance, detect the fault existence, estimate its future impact on system performance and recover the system back to normal. A predictive controller is designed to take proper actions to guarantee the QoS and remedy faults. Experimental studies on a realistic test-bed show the applicability and effectiveness of our approach.

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