Theoretic framework of network feedback control with long delays

It is well known that feedback control may be difficult in a network with long propagation delays (with large bandwidth-delay products). The focus of this article is to provide a theoretical framework of various feedback-based congestion control techniques. Two broad classes of control algorithms are presented: source- and switch (network)-intelligence models. In a source-intelligence model, traffic sources adjust their transmission rates according to congestion information provided by the network. Theoretical models based on queueing theory and delay differential equations are presented. In a network-intelligence model, network switches evaluate appropriate transmission rates of sources. It is believed that any reactive control in a network with long delays is not effective. A control theoretic framework is presented, which attempts to exercise a degree of prediction of traffic patterns in the near future. Algorithms predicting the future input rates and the topological distribution of sources are presented. Finally, a unified approach combining both source- and network-intelligence models may be of interest for further study