In this paper we analyze a class of delayed feedback schemes that achieves the dual goal of keeping buffers small and utilizations high, despite propagation delays and regardless of network rates. We analyze delayed feedback schemes as a system of delay-differential equations, in which we model the queue-length process and the rate at which a source transmits data as fluids. We assume that a stream of acknowledgements carries information about the state of a bottleneck queue back to the source, which adapts its transmission rate according to any monotone function of that state. We show stability for this class of schemes, in that their rate of transmission and queue length rapidly converge to a small neighborhood of the designed operating point. We identify the appropriate scaling of the model's parameters for the system to perform optimally.
In this paper we analyze a class of delayed feedback schemes that achieves the dual goal of keeping buffers small and utilizations high, despite propagation delays and regardless of network rates. We analyze delayed feedback schemes as a system of delay-differential equations, in which we model the queue-length process and the rate at which a source transmits data as fluids. We assume that a stream of acknowledgements carries information about the state of a bottleneck queue back to the source, which adapts its transmission rate according to any monotone function of that state. We show stability for this class of schemes, in that their rate of transmission and queue length rapidly converge to a small neighborhood of the designed operating point. We identify the appropriate scaling of the model's parameters for the system to perform optimally.
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