Skip to main content

Experience-driven research on programmable networks

Author(s): Kim, Hyojoon; Chen, Xiaoqi; Brassil, Jack; Rexford, Jennifer

Download
To refer to this page use: http://arks.princeton.edu/ark:/88435/pr1f27v
Abstract: Many promising networking research ideas in programmable networks never see the light of day. Yet, deploying research prototypes in production networks can help validate research ideas, improve them with faster feedback, uncover new research questions, and also ease the subsequent transition to practice. In this paper, we show how researchers can run and validate their research ideas in their own backyards---on their production campus networks---and we have seen that such a demonstrator can expedite the deployment of a research idea in practice to solve real network operation problems. We present P4Campus, a proof-of-concept that encompasses tools, an infrastructure design, strategies, and best practices---both technical and non-technical---that can help researchers run experiments against their programmable network idea in their own network. We use network tapping devices, packet brokers, and commodity programmable switches to enable running experiments to evaluate research ideas on a production campus network. We present several compelling data-plane applications as use cases that run on our campus and solve production network problems. By sharing our experiences and open-sourcing our P4 apps [28], we hope to encourage similar efforts on other campuses.
Publication Date: 2021
Citation: Kim, Hyojoon, Xiaoqi Chen, Jack Brassil, and Jennifer Rexford. "Experience-driven research on programmable networks." ACM SIGCOMM Computer Communication Review 51, no. 1 (2021): pp. 10-17. doi:10.1145/3457175.3457178
DOI: 10.1145/3457175.3457178
ISSN: 0146-4833
Pages: 10 - 17
Type of Material: Journal Article
Journal/Proceeding Title: ACM SIGCOMM Computer Communication Review
Version: Final published version. Article is made available in OAR by the publisher's permission or policy.



Items in OAR@Princeton are protected by copyright, with all rights reserved, unless otherwise indicated.