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author:

Zhou, Zhengyan (Zhou, Zhengyan.) [1] | Lv, Jingwen (Lv, Jingwen.) [2] | Cheng, Lingfei (Cheng, Lingfei.) [3] | Chen, Xiang (Chen, Xiang.) [4] | Zhang, Tianzhu (Zhang, Tianzhu.) [5] | Huang, Qun (Huang, Qun.) [6] | Luo, Jiayu (Luo, Jiayu.) [7] | Zhu, Longlong (Zhu, Longlong.) [8] | Zhang, Dong (Zhang, Dong.) [9] | Wu, Chunming (Wu, Chunming.) [10]

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CPCI-S EI

Abstract:

Sketches enable efficient and fine-grained network measurement results with configurable resource-performance trade-offs. While sketch configurations are guided by theories, the current theoretical guidelines are either impractical or deficient for sketch configurations on emerging programmable switches. To better configure sketches on programmable switches, we (1) systematically analyze the limitations of sketch configuration guidelines on programmable hardware switches (i.e., unguided parameters, accuracy profiles, and resource budgets); (2) propose a generic and practical framework called SketchGuide to automate efficient sketch configurations on programmable switches; (3) implement SketchGuide on a Barefoot Tofino switch and compare SketchGuide to the state-of-the-art sketches by conducting extensive experiments. Our evaluations demonstrate that SketchGuide can automatically configure unguided parameters given resource budgets. SketchGuide reduces the hardware resource footprint by 52.92%-99.28% compared with current guidelines without impacting fidelity.

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  • [ 1 ] [Zhou, Zhengyan]Zhejiang Univ, Hangzhou, Peoples R China
  • [ 2 ] [Lv, Jingwen]Zhejiang Univ, Hangzhou, Peoples R China
  • [ 3 ] [Chen, Xiang]Zhejiang Univ, Hangzhou, Peoples R China
  • [ 4 ] [Wu, Chunming]Zhejiang Univ, Hangzhou, Peoples R China
  • [ 5 ] [Cheng, Lingfei]Fuzhou Univ, Fuzhou, Peoples R China
  • [ 6 ] [Luo, Jiayu]Fuzhou Univ, Fuzhou, Peoples R China
  • [ 7 ] [Zhu, Longlong]Fuzhou Univ, Fuzhou, Peoples R China
  • [ 8 ] [Zhang, Dong]Fuzhou Univ, Fuzhou, Peoples R China
  • [ 9 ] [Chen, Xiang]Peking Univ, Beijing, Peoples R China
  • [ 10 ] [Huang, Qun]Peking Univ, Beijing, Peoples R China
  • [ 11 ] [Zhang, Tianzhu]Nokia Bell Labs, Holmdel, NJ USA

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2022 IEEE 30TH INTERNATIONAL CONFERENCE ON NETWORK PROTOCOLS (ICNP 2022)

ISSN: 1092-1648

Year: 2022

Cited Count:

WoS CC Cited Count: 7

SCOPUS Cited Count: 7

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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