Abstract: Bag-of-Tasks data-intensive applications in cloud have been appeared in many fields. Considering the decentralized data centers and "pay-on-demand" model for resource usage, these applications now are facing new challenges in data selection. One of the problems is how to choose the appropriate data resources from multiple datasets which have the same content but the different locations and access costs. Firstly, cloud environment and data selection problem were modeled. Based on the model, a cost-minimized data selection process was abstracted as a weighted set covering problem, and a new data selection strategy was proposed to make a tradeoff between execution efficiency and economic cost.Results of experiments show that the strategy takes into consideration both cost optimization and execution efficiency,and achieves a comprehensive performance.

Key words: Cloud computing, Bag-of-Tasks, Data-intensive application, Data selection, Weighted set covering