Grid Workflows are emerging as practical programming models for solving large e-scientific problems on the Grid. However, it is typically assumed that the workflow components either read or write data to conventional files, which are copied from one execution stage to another, or they are tightly coupled using IPC libraries such as MPI or distributed streaming. More flexible communication can be achieved by overloading conventional READ and WRITE operations with advanced IO mechanisms such as sockets, streams and pipes, as is done in the GriddLeS environment. Such flexibility allows the pipelining of temporally dependent components, or in contrast, delaying of tightly coupled computations based on the current resource availability and network connectivity. However, it is also harder to schedule the workflow, because the communication mode may not be decided until run time. In this paper, we propose a new scheduling model that leverages such communication flexibility and allows us to g...