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Service-oriented architecture builds software applications from large numbers of loosely coupled distributed services, while workflow technology coordinates these distributed services to achieve a shared task or goal. Scientific workflow is becoming researching hotspot along with the e-science and cyber-infrastructure applications, which run in the grid environment. Therefore, selection and scheduling of services in scientific workflow are complex and challenging. In utility grid, scientific application uses scheduling strategy to minimize its cost, while service provider adopts pricing schema to maximize its profit. Based on our previous work: pricing schema based on marginal principle (marginal pricing for short in this paper), we introduce a cost-gradient metric to provide criteria for service selection, and then propose a cost minimization scheduling strategy with specified deadline. Moreover, our scheduling environment is totally commercialized by scientific workflow scheduling market model. Results from experiments demonstrate our strategy can optimize usage cost of different types of workflows while satisfying QoS requirements.