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Most Influential SIGCOMM 2017 Paper · 2026-03 edition

SketchVisor: Robust Network Measurement For Software Packet Processing

Qun Huang, Xin Jin, Patrick P. C. Lee, Runhui Li, Lu Tang, Yi-Chao Chen, Gong Zhang

Venue
ACM SIGCOMM Conference (SIGCOMM) 2017
Recognition
Most Influential SIGCOMM 2017 Paper (Rank No. 8)
Edition
2026-03
Impact factor
5
Certificate ID
0369ec0e821ff0e1

Abstract

Network measurement remains a missing piece in today's software packet processing platforms. Sketches provide a promising building block for filling this void by monitoring every packet with fixed-size memory and bounded errors. However, our analysis shows that existing sketch-based measurement solutions suffer from severe performance drops under high traffic load. Although sketches are efficiently designed, applying them in network measurement inevitably incurs heavy computational overhead. We present SketchVisor, a robust network measurement framework for software packet processing. It augments sketch-based measurement in the data plane with a fast path, which is activated under high traffic load to provide high-performance local measurement with slight accuracy degradations. It further recovers accurate network-wide measurement results via compressive sensing. We have built a SketchVisor prototype on top of Open vSwitch. Extensive testbed experiments show that SketchVisor achieves high throughput and high accuracy for a wide range of network measurement tasks and microbenchmarks.

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