RAIL: A Case for Redundant Arrays of Inexpensive Links in Data Center Networks


Danyang Zhuo, University of Washington; Monia Ghobadi, Ratul Mahajan, Amar Phanishayee, and Xuan Kelvin Zou, Microsoft Research; Hang Guan, Columbia University; Arvind Krishnamurthy and Thomas Anderson, University of Washington


While there are many proposals to reduce the cost of data center networks (DCN), little attention has been paid to the role played by the physical links that carry packets. By studying over 300K optical links across many production DCNs, we show that these links are operating quite conservatively relative to the requirements in the IEEE standards. Motivated by this observation, to reduce DCN costs, we propose using transceivers—a key contributor to DCN cost—beyond their currently specified limit. Our experiments with multiple commodity transceivers show that their reach can be “stretched” 1.6 to 4 times their specification. However, with stretching, the performance of 1–5% of the DCN paths can fall below the IEEE standard. We develop RAIL, a system to ensure that in such a network, applications only use paths that meet their performance needs. Our proposal can reduce the network cost by up to 10% for 10Gbps networks and 44% for 40Gbps networks, without affecting the applications’ performance.

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.

Presentation Video

Download Video

Presentation Audio

@inproceedings {201472,
author = {Danyang Zhuo and Monia Ghobadi and Ratul Mahajan and Amar Phanishayee and Xuan Kelvin Zou and Hang Guan and Arvind Krishnamurthy and Thomas Anderson},
title = {{RAIL}: A Case for Redundant Arrays of Inexpensive Links in Data Center 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 = {561--576},
url = {https://www.usenix.org/conference/nsdi17/technical-sessions/presentation/zhuo},
publisher = {{USENIX} Association},