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Most Influential SIGCOMM 2020 Paper · 2026-03 edition

OmniMon: Re-architecting Network Telemetry With Resource Efficiency And Full Accuracy

Qun Huang, Haifeng Sun, Patrick P. C. Lee, Wei Bai, Feng Zhu, Yungang Bao

Venue
ACM SIGCOMM Conference (SIGCOMM) 2020
Recognition
Most Influential SIGCOMM 2020 Paper (Rank No. 14)
Edition
2026-03
Impact factor
4
Certificate ID
b76e23437694e71a

Abstract

Network telemetry is essential for administrators to monitor massive data traffic in a network-wide manner. Existing telemetry solutions often face the dilemma between resource efficiency (i.e., low CPU, memory, and bandwidth overhead) and full accuracy (i.e., error-free and holistic measurement). We break this dilemma via a network-wide architectural design OmniMon, which simultaneously achieves resource efficiency and full accuracy in flow-level telemetry for large-scale data centers. OmniMon carefully coordinates the collaboration among different types of entities in the whole network to execute telemetry operations, such that the resource constraints of each entity are satisfied without compromising full accuracy. It further addresses consistency in network-wide epoch synchronization and accountability in error-free packet loss inference. We prototype OmniMon in DPDK and P4. Testbed experiments on commodity servers and Tofino switches demonstrate the effectiveness of OmniMon over state-of-the-art telemetry designs.

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