Adaptive weighted traffic splitting in programmable data planes

Kuo Feng Hsu, Praveen Tammana, Ryan Beckett, Ang Chen, Jennifer Rexford, David Walker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recent work introduced load-balancing algorithms that dynamically pick the best path entirely in the data plane, to react to traffic dynamics on a small timescale. This paper takes the next step to balance load dynamically across multiple paths in the data plane. The design of such a load-balancing primitive raises interesting challenges due to the hardware constraints of the data plane. We show that these constraints create practical problems for Weighted-Cost MultiPath (WCMP), which replicates hash-table entries in proportion to the weight of each path. Under these hardware constraints, naive implementations of WCMP take a long time to converge to new weights. We then present a hash-based data structure that achieves adaptive traffic splitting in programmable data planes. Our data structure carefully partitions the arithmetic operations required to a) split traffic in proportion to the path weights and b) update the path weights, by leveraging a multi-stage pipeline and stateful ALUs. By doing so, accurate splitting and efficient updates are done at line rate. We implement our data structure in P4 and our preliminary evaluation shows significant reduction in flow completion time compared to other data-plane load-balancing schemes such as HULA.

Original languageEnglish (US)
Title of host publicationSOSR 2020 - Proceedings of the 2020 Symposium on SDN Research
PublisherAssociation for Computing Machinery, Inc
Pages103-109
Number of pages7
ISBN (Electronic)9781450371018
DOIs
StatePublished - Mar 3 2020
Event2020 Symposium on SDN Research, SOSR 2020 - San Jose, United States
Duration: Mar 3 2020 → …

Publication series

NameSOSR 2020 - Proceedings of the 2020 Symposium on SDN Research

Conference

Conference2020 Symposium on SDN Research, SOSR 2020
CountryUnited States
CitySan Jose
Period3/3/20 → …

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

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