Database tuning is a common problem, but it requires much knowledge about the characteristics of the database system and the expected workload. Dynamically changing workload complicates the search for the perfect settings. In this contribution we present several approaches that autonomously examine the operations and adjust different parameters. Even though different tools for this task are ava...

This paper presents a new fault tolerant control scheme for unknown multivariable stochastic systems by modifying the conventional state-space self-tuning control approach. For the detection of faults, a quantitative criterion is developed by comparing the innovation process errors occurring in the Kalman filter estimation algorithm, which, for faulty system recovery, a weighting matrix resetti...

Performance tuning in modern database systems requires a lot of expertise, is very time consuming and often misdirected. Tuning attempts often lack a methodology that has a holistic view of the database. The absence of historical diagnostic information to investigate performance issues at first occurrence exacerbates the whole tuning process often requiring that problems be reproduced before th...