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Intelligent sensor devices together with data stream management systems allow the automatic recording and processing of huge data volumes to guide any kind of process control or business decision. However, a crucial problem is posed by data quality deficiencies due to imprecise sensors, environmental influences, transfer failures, etc. If not handled carefully, they misguide decisions and lead to inappropriate reactions. In this paper, the authors present the quality-driven optimization of stream processing that improves the resulting quality of data and service. After an introduction to data quality management in data streams, they define the targeted optimization problem comprising the optimization objectives and parameters that configure the required stream processing operators.
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