In this report, we consider the problem of scheduling streaming applications described by complex task graphs on a heterogeneous multi-core platform, the IBM QS 22 platform, embedding two STI Cell BE processor. We first derive a complete computation and communication model of the platform, based on comprehensive benchmarks. Then, we use this model to express the problem of maximizing the throughput of a streaming application on this platform. Although the problem is proven NP-complete, we present an optimal solution based on mixed linear programming. We also propose simpler scheduling heuristics to compute mapping of the application task-graph on the platform. We then come back to the platform, and propose a scheduling software to deploy streaming applications on this platform. This allows us to thoroughly test our scheduling strategies on the real platform. We thus show that we are able to achieve a good speed-up, either with the mixed linear programming solution,