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Measuring the Effects of Data Distribution Models on Performance Evaluation of Distributed Database Systems

The effect of simplistic assumptions about the data distribution and replication in a system on performance measures and the computational complexity and accuracy of evaluations of performance measures is investigated. The size of the participating node set of a transaction is chosen as the desired performance measure. A data distribution and replication model is represented by four key parameters. Probabilistic analysis is used to evaluate six of these models. It is concluded that even though some of the data distribution and replication models appear to be simplistic, the results obtained from them are very close to those from complex models. In addition, the gains due to drastically reduced execution times strongly suggest the use of simple models (at least) in the early stages of the design process. >