Predictive flow control for TCP-friendly end-to-end real-time video on the Internet

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In order to cope with time-varying conditions in networks with no or limited QoS support like the current Internet, schemes have been proposed for real-time applications to dynamically adjust traffic sources' data sending rate. However, employing adaptive rate control may not be sufficient to prevent or handle network congestion. As most of the real-time applications are based on RTP/UDP protocols, an issue of possibly unfair sharing of bandwidth between TCP and UDP applications has been raised. In this paper, we propose an application-level control protocol called Real-time Rate and Retransmission Control Protocol Plus in which several control mechanisms are used and integrated to maximize the delivery performance of UDP-based real-time continuous media over the Internet while friendly sharing network bandwidth with TCP connections. Here we propose to use adaptive filters in network state characterization and inference. Both simulation and actual implementation performance results show that recursive least square-based adaptive prediction makes good use of past measurement in forecasting future condition and effectively avoids network congestion. It also shows that the scheme achieves reasonably friendly resource sharing with TCP connections.