Flexile: meeting bandwidth objectives almost always.

Wide-area cloud provider networks must support the bandwidth requirements of network traffic despite failures. Existing traffic engineering (TE) schemes perform no better than an approach that optimally routes traffic for each failure scenario. We show that this results in sub-optimal routing decisions that hurt performance, and are potentially unfair to some traffic across scenarios. To tackle this, we develop Flexile , which exploits and discovers opportunities to improve network performance by prioritizing certain traffic in each failure state so that it can meet its bandwidth requirements. Flexile seeks to minimize a desired percentile of loss across all traffic flows, while modeling diverse needs of different traffic classes. To achieve this, Flexile consists of (i) an offline phase that identifies which failure states are critical for each flow; and (ii) an online phase, which on failure allocates bandwidth prioritizing critical flows for that failure state, while also judiciously allocating bandwidth to non-critical flows. For tractability, Flexile 's offline phase uses a decomposition algorithm aided with problem-specific accelerations. Evaluations using real topologies, and validated with emulation testbed experiments, show that Flexile outperforms state-of-the-art TE schemes including SWAN, SMORE, and Teavar in reducing flow loss at desired percentiles by 46% or more in the median case.