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 language||English (US)|
|Title of host publication||INFOCOM 2022 - IEEE Conference on Computer Communications|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||10|
|State||Published - 2022|
|Event||41st IEEE Conference on Computer Communications, INFOCOM 2022 - Virtual, Online, United Kingdom|
Duration: May 2 2022 → May 5 2022
|Name||IEEE INFOCOM 2022 - IEEE Conference on Computer Communications|
|Conference||41st IEEE Conference on Computer Communications, INFOCOM 2022|
|Period||5/2/22 → 5/5/22|
Bibliographical noteFunding 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
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