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Our research addresses the efficient transfer of large data across wide-area networks, focusing on applications like remote visualization and real-time collaboration. To attain high performance in the real-time exchange of data across collaborating machines and end users, we are developing and evaluating methods and techniques for coordinating application-level with network transport-level adaptations of data communication. Specifically, complementing previous work on TCP-friendly communication and on adaptive transport protocols, our approach is to strongly coordinate application-level with transport-level changes in communication behavior, so as to best meet application needs without violating fairness in network resource usage. The approach is evaluated with the IQ-ECho middleware, which implements the distribution of scientific data to remote collaborators. Using IQ-ECho, application-level adaptations like selective data down-sampling are triggered by transport-level information provided by the instrumented IQ-RUDP protocol underlying IQ-ECho's communications. The application- to network-layer exchange of information necessary for such coordinated adaptations is implemented with ECho attributes, which provide a lightweight way for an application to provide quality of service information and to describe its adaptation to the transport layer.