On efficient on-line grouping of flows with shared bottlenecks at loaded servers

We design an efficient on-line approach, FlowMate, for partitioning flows at a busy server into flow groups that share bottlenecks. These groups are periodically input to congestion coordination, aggregation, load balancing, admission control, or pricing modules. FlowMate uses in-band packet delay measurements to the receivers to determine shared bottlenecks among flows. Packet delay information is piggybacked on returning feedback, or, if impossible, flow (e.g., TCP) round trip time estimates are used. We simulate FlowMate to examine the effect of network load, traffic burstiness, network buffer sizes, and packet drop policies on partitioning correctness. Our results demonstrate accurate partitioning of medium to long-lived flows even under heavy load and self-similar background traffic. Experiments with HTTP/1.1 flows demonstrate difficulties in partitioning bursty foreground traffic. We also study fairness of coordinated congestion management when integrated with FlowMate.