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Multirate multicast improves user quality but complicates network optimization. This paper introduces a novel control scheme to dynamically optimize multirate multicast. We present MMT, an adaptive policy which combines differential backlog scheduling and intelligent packet dropping, both based on local information. MMT is shown to maximize network throughput by adapting to changing conditions such...
We consider utility maximization in networks where the sources do not employ flow control and may consequently overload the network. In the absence of flow control at the sources, some packets will inevitably have to be dropped when the network is in overload. To that end, we first develop a distributed, threshold-based packet dropping policy that maximizes the weighted sum throughput. Next, we consider...
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