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As more and more workflow applications are deployed in the cloud, how to optimize resource scheduling cost while satisfying workflow deadline constraints is a popular research area. In this paper, we propose a cost optimization with deadline constraint (CODC) algorithm. Firstly, workflow tasks are merged to reduce the data transfer overhead between different instances. Secondly, paying attention to the impact of parent and subtasks on the priority of the current task, the case of unmet task sub-deadlines is considered to select the instance that completes task execution earliest. Finally, the experimental results are compared with the existing algorithms on five workflows. CODC algorithm has a lower workflow execution cost compared to other three comparison algorithms. [ABSTRACT FROM AUTHOR]