Using Explicit (Host-to-Network) Flow Measurements for Network Tomography

QUIC hides implicit protocol semantics commonly used for flow performance measurements with TCP. Addressing this challenge, Explicit (Host-to-Network) Flow Measurement (EFM) schemes explicitly expose measurable signals: QUIC's spin bit enables latency measurements, and RFC 9506 defines mechanisms for packet loss. While the measurement accuracy of these schemes has already been studied, their utility for network management is unexplored. In this work, we demonstrate that EFM can enable network tomography (NT), which traditionally uses active measurements. Comparing EFM-based to traditional NT through extensive network simulations, we find that raw EFM output challenges NT due to fluctuations induced by links outside the monitored network. However, path segmentation capabilities of the spin and Q bits can remedy these issues. Overall, our findings highlight the general potential of EFM for network management.

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Publication Details

Published
2025-07-14
DOI
https://doi.org/10.1145/3744200.3744769
Primary Topic
Network Traffic and Congestion Control
Type
article
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article

Using Explicit (Host-to-Network) Flow Measurements for Network Tomography

Constantin Sander, Ike Kunze, Niklas Rieken, Klaus Wehrle et al.
Network Traffic and Congestion Control
article

Using Explicit (Host-to-Network) Flow Measurements for Network Tomography

Constantin Sander, Ike Kunze, Niklas Rieken, Klaus Wehrle, Andreas Ruhrmann
article en

Abstract

QUIC hides implicit protocol semantics commonly used for flow performance measurements with TCP. Addressing this challenge, Explicit (Host-to-Network) Flow Measurement (EFM) schemes explicitly expose measurable signals: QUIC's spin bit enables latency measurements, and RFC 9506 defines mechanisms for packet loss. While the measurement accuracy of these schemes has already been studied, their utility for network management is unexplored. In this work, we demonstrate that EFM can enable network tomography (NT), which traditionally uses active measurements. Comparing EFM-based to traditional NT through extensive network simulations, we find that raw EFM output challenges NT due to fluctuations induced by links outside the monitored network. However, path segmentation capabilities of the spin and Q bits can remedy these issues. Overall, our findings highlight the general potential of EFM for network management.

RWTH Aachen University (DE)
Openalex Percentile: Top 81%
Network Traffic and Congestion Control
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