NFlow and MVT Abstractions for NFV Scaling

Ziyan Wu, Yang Zhang, Wendi Feng, Zhi Li Zhang

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

Abstract

The ability to dynamically scale in/out network functions (NFs) on multiple cores/servers to meet traffic demands is a key benefit of network function virtualization (NFV). The stateful NF operations make NFV scaling a challenging task: if care is not taken, NFV scaling can lead to incorrect operations and poor performance. We advocate two general abstractions, NFlow and Match-Value Table (MVT), for NFV packet processing pipelines. We present formal definitions of the abstractions and discuss how they can facilitate NFV scaling by minimizing or eliminating shared states. Using NFs implemented with the proposed abstractions, we conduct extensive experiments and demonstrate their efficacy in terms of correctness and performance of NFV scaling.

Original languageEnglish (US)
Title of host publicationINFOCOM 2022 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages180-189
Number of pages10
ISBN (Electronic)9781665458221
DOIs
StatePublished - 2022
Event41st IEEE Conference on Computer Communications, INFOCOM 2022 - Virtual, Online, United Kingdom
Duration: May 2 2022May 5 2022

Publication series

NameIEEE INFOCOM 2022 - IEEE Conference on Computer Communications

Conference

Conference41st IEEE Conference on Computer Communications, INFOCOM 2022
Country/TerritoryUnited Kingdom
CityVirtual, Online
Period5/2/225/5/22

Bibliographical note

Funding Information:
ACKNOWLEDGEMENT The research was supported in part by NSF under Grants CNS-1814322, CNS-1831140, CNS-1836772, CNS-1901103, CNS-2106771 and CCF-2123987.C

Publisher Copyright:
© 2022 IEEE.

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