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Datacenter applications demand both low latency and high throughput; whileinteractive applications (e.g., Web Search) demand low tail latency for theirshort messages due to their partition-aggregate software architecture, manydata-intensive applications (e.g., Map-Reduce) require high throughput for longflows as they move vast amounts of data across the network. Recent proposalsimprove latency of short flows and throughput of long flows by addressing theshortcomings of existing packet scheduling and congestion control algorithms,respectively. We make the key observation that long tails in the FlowCompletion Times (FCT) of short flows result from packets that suffercongestion at more than one switch along their paths in the network. Ourproposal, Slytherin, specifically targets packets that suffered from congestionat multiple points and prioritizes them in the network. Slytherin leverages ECNmechanism which is widely used in existing datacenters to identify such tailpackets and dynamically prioritizes them using existing priority queues. Ascompared to existing state-of-the-art packet scheduling proposals, Slytherinachieves 18.6% lower 99th percentile flow completion times for short flowswithout any loss of throughput. Further, Slytherin drastically reduces 99thpercentile queue length in switches by a factor of about 2x on average.

Slytherin: Dynamic, Network-assisted Prioritization of Tail Packets in Datacenter Networks