Computer network congestion control algorithms control the sending rate for flows of data from sender network nodes to receiver network nodes. These algorithms attempt to utilize network bandwidth capacity efficiently, while keeping network data loss rates low, and allocating network capacity between different flows sharing the network in an approximately fair manner, or at least avoiding starvation of some flows. In addition, some congestion control algorithms attempt to keep network queues short, to reduce queuing delays and further reduce loss rates.
This disclosure describes model-based congestion control, a technique that explicitly models the network conditions along the path(s) between senders and receivers. The algorithm updates the model using measurements obtained from the packets in the flow it is controlling. The algorithm uses those measurements as inputs to update the model and then uses that model to control its sending process. This model-based approach can allow the congestion control algorithm to achieve higher throughputs and/or lower delays and/or lower data packet loss rates than would be achievable by other techniques.
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Cardwell, Neal; Jacobson, Van; Cheng, Yuchung; Yeganeh, Soheil Hassas; Vasiliev, Victor; Swett, Ian; Jha, Priyaranjan; Seung, Yousuk; and Wetherall, David, "Model-based Network Congestion Control", Technical Disclosure Commons, (March 27, 2019)