Precise Data Center Traffic Engineering with Constrained Hardware Resources


Shawn Shuoshuo Chen, Carnegie Mellon University; Keqiang He, AirBNB; Rui Wang, Google; Srinivasan Seshan and Peter Steenkiste, Carnegie Mellon University


Data center traffic engineering (TE) routes flows over a set of available paths following custom weight distributions to achieve optimal load balancing or flow throughput. However, as a result of hardware constraints, it is challenging, and often impossible for larger data center networks, to precisely implement the TE weight distributions on the data plane switches. The resulting precision loss in the TE implementation causes load imbalances that can result in congestion and traffic loss.

Instead of treating all flows equally, we adapt the hardware resource allocation to a flow’s traffic volume and its contribution to the overall precision loss. We intelligently prune select ports in weight distributions and merge identical distributions to free up hardware resources. Evaluation using realistic traffic loads shows that our techniques approximate ideal TE solutions under various scenarios within 7% error, compared to a 67% error for today’s state-of-the-art approach. In addition, our design avoids traffic loss triggered by switch rule overflow. Finally, the execution time is 10× faster than the current approach.

NSDI '24 Open Access Sponsored by
King Abdullah University of Science and Technology (KAUST)

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

@inproceedings {295541,
author = {Shawn Shuoshuo Chen and Keqiang He and Rui Wang and Srinivasan Seshan and Peter Steenkiste},
title = {Precise Data Center Traffic Engineering with Constrained Hardware Resources},
booktitle = {21st USENIX Symposium on Networked Systems Design and Implementation (NSDI 24)},
year = {2024},
isbn = {978-1-939133-39-7},
address = {Santa Clara, CA},
pages = {669--690},
url = {},
publisher = {USENIX Association},
month = apr