Optimization of materialization strategies for derived data elements

The research in materialization of derived data elements has dealt so far with the if issue of whether to physically store derived data elements. In the active database area, there has been some research on the how issue. We deal with the when issue, devising an optimization model to determine the optimal materialization strategy. The decision problem confronted by the optimization model deals with devising the materialization strategy that consists of a set of interdependent decisions about each derived data element. Each decision relates to two issues: Should the value of a derived data element be persistent? What is the required level of consistency of a derived value with respect to its derivers? For each derived data element, the decision is based on both its local properties and its interdependencies with other derived values. The optimization model is based on a heuristic algorithm that finds a local optimum in O(N²) and a monitor that obtains feedback about the actual database performance. This optimization model is general and is not specific to any data model. Our experimental results show that a predictor for the optimal solution cannot be obtained in any intuitive or analytic way, due to the complexity of the involved considerations; thus, there is no obvious way to achieve these results without using the optimization model. This fact is a strong motivation for applying such an optimization model