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Characterizing Anycast Flipping: Prevalence and Impact

Publication ,  Conference
Zhang, X; Lin, S; Huang, T; Maggs, BM; Schomp, K; Yang, X
Published in: Lecture Notes in Computer Science
January 1, 2025
Published version (DOI)

A 2016 study by Wei and Heidemann showed that anycast routing of DNS queries to root name servers is fairly stable, with only 1% of RIPE Atlas vantage points “flipping” back and forth between different root name server sites. Continuing this study longitudinally, however, we observe that among the vantage points that collected data continuously from 2016 to 2024 the fraction that experience flipping has increased from 0.8% to 3.2%. Given this apparent increase, it is natural to ask how much anycast flipping impacts the performance of everyday tasks such as web browsing. To measure this impact, we established a mock web page incorporating many embedded objects on an anycast-based CDN and downloaded the page from geographically distributed BrightData vantage points. We observed that packets within individual TCP flows almost always reach the same site, but different flows may flip to different sites. We found that 1,988 (10.9%) of 18,294

Duke Scholars

Xiaowei Yang
Author Xiaowei Yang Computer Science
Bruce Maggs
Author Bruce Maggs Computer Science

Published In

Lecture Notes in Computer Science

DOI

10.1007/978-3-031-85960-1_15

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2025

Volume

15567 LNCS

Start / End Page

361 / 388

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Zhang, X., Lin, S., Huang, T., Maggs, B. M., Schomp, K., & Yang, X. (2025). Characterizing Anycast Flipping: Prevalence and Impact. In Lecture Notes in Computer Science (Vol. 15567 LNCS, pp. 361–388). https://doi.org/10.1007/978-3-031-85960-1_15
Zhang, X., S. Lin, T. Huang, B. M. Maggs, K. Schomp, and X. Yang. “Characterizing Anycast Flipping: Prevalence and Impact.” In Lecture Notes in Computer Science, 15567 LNCS:361–88, 2025. https://doi.org/10.1007/978-3-031-85960-1_15.
Zhang X, Lin S, Huang T, Maggs BM, Schomp K, Yang X. Characterizing Anycast Flipping: Prevalence and Impact. In: Lecture Notes in Computer Science. 2025. p. 361–88.
Zhang, X., et al. “Characterizing Anycast Flipping: Prevalence and Impact.” Lecture Notes in Computer Science, vol. 15567 LNCS, 2025, pp. 361–88. Scopus, doi:10.1007/978-3-031-85960-1_15.
Zhang X, Lin S, Huang T, Maggs BM, Schomp K, Yang X. Characterizing Anycast Flipping: Prevalence and Impact. Lecture Notes in Computer Science. 2025. p. 361–388.

Published In

Lecture Notes in Computer Science

DOI

10.1007/978-3-031-85960-1_15

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2025

Volume

15567 LNCS

Start / End Page

361 / 388

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences