Abstract

We present SWAN, a system that boosts the utilization of inter-datacenter networks by centrally controlling when and how much trac each service sends and frequently re-con guring the network’s data plane to match current trac demand. But done simplistically, these re-con gurations can also cause severe, transient congestion because different switches may apply updates at different times. We develop a novel technique that leverages a small amount of scratch capacity on links to apply updates in a provably congestion-free manner, without making any assumptions about the order and timing of updates at individual switches. Further, to scale to large networks in the face of limited forwarding table capacity, SWAN greedily selects a small set of entries that can best satisfy current demand. It updates this set without disrupting trac by leveraging a small amount of scratch capacity in forwarding tables. Experiments using a testbed prototype and data-driven simulations of two production networks show that SWAN carries 60% more trac than the current practice.