Flowtune: Flowlet Control for Datacenter Networks


Jonathan Perry, Hari Balakrishnan, and Devavrat Shah, Massachusetts Institute of Technology


Rapid convergence to a desired allocation of network resources to endpoint traffic is a difficult problem. The reason is that congestion control decisions are distributed across the endpoints, which vary their offered load in response to changes in application demand and network feedback on a packet-by-packet basis. We propose a different approach for datacenter networks, flowlet control, in which congestion control decisions are made at the granularity of a flowlet, not a packet. With flowlet control, allocations have to change only when flowlets arrive or leave. We have implemented this idea in a system called Flowtune using a centralized allocator that receives flowlet start and end notifications from endpoints. The allocator computes optimal rates using a new, fast method for network utility maximization, and updates endpoint congestion-control parameters. Experiments show that Flowtune outperforms DCTCP, pFabric, sfqCoDel, and XCP on tail packet delays in various settings, converging to optimal rates within a few packets rather than over several RTTs. Benchmarks on an EC2 deployment show a fairer rate allocation than Linux’s Cubic. A data aggregation benchmark shows 1.61x lower p95 coflow completion time.

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@inproceedings {201563,
author = {Jonathan Perry and Hari Balakrishnan and Devavrat Shah},
title = {Flowtune: Flowlet Control for Datacenter Networks},
booktitle = {14th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 17)},
year = {2017},
isbn = {978-1-931971-37-9},
address = {Boston, MA},
pages = {421--435},
url = {https://www.usenix.org/conference/nsdi17/technical-sessions/presentation/perry},
publisher = {{USENIX} Association},
month = mar,

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