Perfect is the Enemy of Good: Lloyd-Max Quantization for Rate Allocation in Congestion Control Plane

Abstract

Decoupling congestion control plane from datapath expedites the development of new congestion control solutions and creates opportunities for explicit rate allocation schemes. However, dealing with large numbers of flows remains a major challenge. Max-min fairness - the gold standard for rate allocation - has a running complexity proportional to the number of flows, which might be prohibitive in large-scale networks. To accelerate explicit rate allocation, we suggest using rate quantization, i.e. mapping the continuous range of flow rates to a small number of bins. We use Lloyd-max, a quantization method that generates bins according to the distribution of flow rates, to dynamically adjust the quantization bins over time. Our experimental evaluation shows that the distortion caused by this quantization scheme is small, while reducing the max-min rate allocation running time by 60 − 90%.