Optimal anticipative congestion control of flows with time-varying input stream ?
This paper is concerned with a new type of congestion control method that we call anticipative congestion control, which exploits probabilistic information available at a network node about congestion at other nodes. Motivated by the Internet flows behaving according to the Transmission Control Protocol, we consider a flow with time-varying input stream. We design a Markov decision process model for flow admission control and characterize the Whittle index in a closed form. This index measures the efficiency of flow data transmission at a router. We prove that such an index policy is optimal and that it further implies optimality of threshold policies. We apply the results to obtain an expression of the index for a single-bottleneck flow under several types of fairness criteria.
congestion control markov decision process whittle index threshold policy fairness restless bandits active queue management transmission control protocol (tcp) explicit congestion notification (ecn)