The authors consider the use of a database cluster with lazy replication. In this paper, controlling the quality of replicated data based on users' requirements is important to improve performance. However, existing approaches are limited to a particular aspect of data quality. The authors propose a general model of data quality which makes the difference between "Freshness" and "Validity" of data. Data quality is expressed through divergence measures from the data with perfect quality. Users can thus specify the minimum level of quality for their queries. This information can be exploited to optimize query load balancing.
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