We present Network Congestion Feedback (NCF), a novel congestion control framework that leverages programmable data planes for generating a rich congestion signal for use in the public Internet. NCF makes several contributions, including isolating ‘mice’ and ‘elephant’ flows using separate queues, detecting congestion in the elephants’ queue and generating a rich sub-RTT signal for the concerned senders, and designing a congestion-control algorithm (CCA) that matches a flow’s demands with supply (i.e., available bandwidth) for maximizing utilization and fairness. It extends two key ingredients from prior work on datacenter CCAs–a short control-loop delay and a precise congestion signal–that are crucial for designing an efficient, fair CCA, by adapting them for the more challenging Internet context. NCF isolates mice and elephant flows so that the former cannot unfairly degrade the throughput of the latter, and it guarantees that mice flows experience minimal round-trip times (RTTs) even when contending with elephant flows. NCF virtually eliminates slow-start spikes and achieves high fairness in both shallow and deep-buffer configurations, and even when the flows experience drastically different RTTs. Lastly, NCF offers low flow completion times (FCTs) to short flows even in challenging multiple-bottleneck scenarios.

The prevailing wisdom is that a software-defined network (SDN) operates under the premise that the logically centralized control plane has an accurate representation of the actual data plane state. Unfortunately, bugs, misconfigurations, faults or attacks can introduce inconsistencies between the network control and the data plane that can undermine the correct operation at runtime. Through our experiments, we realize that P4 SDNs are no exception, and are prone to similar problems. With the aim to verify the control-data plane inconsistency, we present the design and implementation of P4Consist, a system to detect the inconsistency between control and data plane in P4 SDNs. P4Consist generates active probe-based traffic continuously or periodically as an input to the P4 SDNs to check whether the actual behavior on the data plane corresponds to the expected control plane behavior. In P4Consist, the control plane and the data plane generate independent reports which are later, compared to verify the control-data plane consistency. The previous works in the field of monitoring and verification mostly aim to test the P4 programs through static analysis and thus, are insufficient to verify the network consistency at runtime. Experiments with our prototype implementation of P4Consist are promising and show that P4Consist can verify the control-data plane consistency in the complex datacenter 4-ary fat-tree (20 switches) and multipath grid (4, 9 and 16 switches) topologies with 60k rules per switch within a minimum time of 4 minutes. At the same time, P4Consist scales to multiple source-destination pairs to detect control-data plane inconsistency.