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Web service-based workflow management systems have garnered considerable attention for automating and scheduling dependent operations. Such systems often support user preferences, e.g., time of completion, but with the rebirth of distributed computing via the grid/cloud, new challenges are abound: multiple disparate data sources, networks, nodes, and the potential for moving very large datasets. In this paper, we present a framework for integrating QoS support in a service workflow composition system. The relationship between workflow execution time and accuracy is exploited through an automatic workflow composition scheme. The algorithm, equipped with a framework for defining cost models on service completion times and error propagation, composes service workflows which can adapt to user's QoS preferences.