Communication costs represent a significant portion of the execution time of most distributed applications. Thus, it is important to optimize the communication behavior of the algorithm to match the capabilities of the underlying communication fabric. Traditionally, optimizations to the communication behavior have been carried out statically and at the application level (optimizing partitioning, using the most appropriate communication protocols, etc). This paper introduces a new class of optimizations to communication: active run-time matching between the application communication behavior and the communication layer. We propose an active layer extension to the Message Passing Interface (MPI) that dynamically reduces the average communication overhead associated with message sends and receives. The active layer uses dynamic message aggregation to reduce the send overheads and infrequent polling to reduce the receive overhead of messages. The performance of the active layer is evaluated using a number of applications.