The Internet has witnessed a rapid growth in deployment of data-driven overlay network (DON) based streaming applications during recent years. In these applications, each node independently selects some other nodes as its neighbors (i.e. overlay construction), and exchanges streaming data with these neighbors (i.e. data scheduling). This scheme improves the robustness of the system. However, most of the work in the literature focused on the construction problem, and very few addressed its scheduling problem which is also very important for the overall performance. In this paper, we analytically study the scheduling problem in DON and model it as a classical min-cost network flow problem. We then propose both the global optimal scheduling scheme and distributed heuristic algorithm to maximize the system throughput. Experimental results indicate that our algorithms outperform other schemes and the throughput gain is up to 80%.