Fury Route: Leveraging CDNs to Remotely Measure Network Distance

Marcel Flores*, Alexander Wenzel, Kevin Chen, Aleksandar Kuzmanovic

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


Estimating network distance between arbitrary Internet endpoints is an essential primitive in applications ranging from performance optimization to network debugging and auditing. Enabling such a primitive without deploying new infrastructure was demonstrated via DNS. However, the proliferation of DNS hosting has made DNS-based measurement techniques far less dependable. In this paper, we show that the heterogeneous infrastructure of different CDNs, combined with the proliferation of the EDNS0 client-subnet extension (ECS), enables novel infrastructureless measurement. We design Fury Route, a system that estimates network distance by utilizing ECS to construct a virtual path between endpoints via intermediate CDN replicas. Fury Route requires no additional infrastructure to be deployed. The measured endpoints do not need to participate by sending or responding to probes. Fury Route further generates no load on endpoints. It only queries DNS, whose infrastructure is designed for large loads. We extensively evaluate Fury Route and demonstrate that (i) the key to Fury Route’s ability to construct virtual paths lies in the heterogeneity of the underlying CDNs, (ii) Fury Route is effective in revealing relative network distance, needed in many real-world scenarios, (iii) caching can dramatically reduce Fury Route’s DNS overhead, making it a useful system in practice.

Original languageEnglish (US)
Title of host publicationPassive and Active Measurement - 19th International Conference, PAM 2018, Proceedings
EditorsAnja Feldmann, Georgios Smaragdakis, Robert Beverly
PublisherSpringer Verlag
Number of pages13
ISBN (Print)9783319764801
StatePublished - 2018
Event19th International Conference on Passive and Active Measurement, PAM 2018 - Berlin, Germany
Duration: Mar 26 2018Mar 27 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10771 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other19th International Conference on Passive and Active Measurement, PAM 2018

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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