Skip to main content
SpringerLink
Log in

Following the Data Trail: An Analysis of IXP Dependencies

  • Conference paper
  • First Online:
Passive and Active Measurement (PAM 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14538))

Included in the following conference series:

  • 79 Accesses

Abstract

Internet exchange points (IXPs) play a vital role in the modern Internet. Envisioned as a means to connect physically close networks, they have grown into large hubs connecting networks from all over the world, either directly or via remote peering. It is therefore important to understand the real footprint of an IXP to quantify the extent to which problems (e.g., outages) at an IXP can impact the surrounding Internet topology. An IXP footprint computed only from its list of members as given by PeeringDB, or the IXP’s website, is usually depicting an incomplete view of the IXP as it misses downstream networks whose traffic may transit via an IXP although they are not directly peering there. In this paper we propose a robust approach that uncovers this dependency using traceroute data from two large measurement platforms. Our approach converts traceroutes to paths that include both autonomous systems (ASes) and IXPs and computes AS Hegemony to infer their inter-dependencies. This technique discovers thousands of dependent networks not directly connected to IXPs and emphasizes the role of IXPs in the Internet topology. We also look at the geolocation of members and dependents and find that only \({3}{\%}\) of IXPs with dependents are entirely local: all members and dependents are in the same country as the IXP. Another \({52}{\%}\) connect international members, but only have domestic dependents.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Measurement IDs for IPv4: 5051 and 5151.

  2. 2.

    Number of ASes with a customer cone \(> 1\) according to [3].

References

  1. Alice-LG - Your friendly looking glass. https://github.com/alice-lg/alice-lg

  2. AWS: Settlement Free Peering Policy. https://aws.amazon.com/peering/policy/

  3. CAIDA AS Rank. http://as-rank.caida.org/

  4. The CAIDA UCSD IPv4 Routed /24 Topology Dataset - 2022–09-01 - 2022–09-30. https://www.caida.org/catalog/datasets/ipv4_routed_24_topology_dataset/

  5. Cloudflare Peering Policy. https://www.cloudflare.com/peering-policy/

  6. IHR Archive. https://ihr-archive.iijlab.net/

  7. LINX LON1 Outage - March 2021. https://web.archive.org/web/20221206083420/https://www.linx.net/incidents-log/

  8. Peering with Meta. https://www.facebook.com/peering/

  9. PeeringDB. https://www.peeringdb.com/

  10. Prerequisites to Peer with Google. https://peering.google.com/#/options/peering

  11. University of Oregon Route Views Project. http://www.routeviews.org/

  12. Follow-up on previous incident at AMS-IX platform, May 2015. https://web.archive.org/web/20160327075404/https://ams-ix.net/newsitems/195

  13. Outage on Amsterdam peering platform, November 2023. https://www.ams-ix.net/ams/outage-on-amsterdam-peering-platform

  14. Aben, E.: Measuring More Internet with RIPE Atlas, January 2016. https://labs.ripe.net/author/emileaben/measuring-more-internet-with-ripe-atlas/

  15. Aben, E.: Does The Internet Route Around Damage? - Edition 2021, April 2021. https://labs.ripe.net/author/emileaben/does-the-internet-route-around-damage-edition-2021/

  16. Ahmed, A., Shafiq, Z., Bedi, H., Khakpour, A.: Peering vs. transit: performance comparison of peering and transit interconnections. In: International Conference on Network Protocols (ICNP), pp. 1–10. IEEE (2017). https://doi.org/10.1109/ICNP.2017.8117549

  17. Alfroy, T., Holterbach, T., Pelsser, C.: MVP: Measuring Internet Routing from the Most Valuable Points. In: Internet Measurement Conference (IMC), pp. 770–771. ACM (2022). https://doi.org/10.1145/3517745.3563031

  18. Appel, M., Aben, E., Fontugne, R.: Metis: better atlas vantage point selection for everyone. In: Network Traffic Measurement and Analysis Conference (TMA). IFIP (2022)

    Google Scholar 

  19. Arnold, T., et al.: Cloud provider connectivity in the flat internet. In: Internet Measurement Conference (IMC), pp. 230–246. ACM (2020). https://doi.org/10.1145/3419394.3423613

  20. Bajpai, V., Eravuchira, S.J., Schönwälder, J.: Lessons learned from using the RIPE atlas platform for measurement research. ACM SIGCOMM Comput. Commun. Rev. 45(3), 35–42 (2015). https://doi.org/10.1145/2805789.2805796

    Article  Google Scholar 

  21. Bajpai, V., Eravuchira, S.J., Schönwälder, J., Kisteleki, R., Aben, E.: Vantage point selection for IPv6 measurements: benefits and limitations of RIPE atlas tags. In: IFIP/IEEE Symposium on Integrated Network and Service Management (IM), pp. 37–44. IEEE (2017). https://doi.org/10.23919/INM.2017.7987262

  22. Bertholdo, L.M., Ceron, J.M., Granville, L.Z., van Rijswijk-Deij, R.M.: Forecasting the impact of IXP outages using Anycast. In: Network Traffic Measurement and Analysis Conference (TMA). IFIP (2021)

    Google Scholar 

  23. Brito, S.H.B., Santos, M.A.S., Fontes, R.R., Perez, D.A.L., Rothenberg, C.E.: Dissecting the largest national ecosystem of public Internet eXchange Points in Brazil. In: Karagiannis, T., Dimitropoulos, X. (eds.) PAM 2016. LNCS, vol. 9631, pp. 333–345. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-30505-9_25

    Chapter  Google Scholar 

  24. Böttger, T., et al.: Shaping the Internet: 10 Years of IXP Growth (2018). https://doi.org/10.48550/ARXIV.1810.10963

  25. Böttger, T., Cuadrado, F., Tyson, G., Castro, I., Uhlig, S.: Open connect everywhere: a glimpse at the internet ecosystem through the lens of the Netflix CDN. ACM SIGCOMM Comput. Commun. Rev. 48(1), 28–34 (2018). https://doi.org/10.1145/3211852.3211857

    Article  Google Scholar 

  26. Chang, H., Jamin, S., Willinger, W.: Inferring AS-level internet topology from router-level path traces. In: Scalability and Traffic Control in IP Networks, vol. 4526, pp. 196–207. SPIE (2001). https://doi.org/10.1117/12.434395

  27. Chatzis, N., Smaragdakis, G., Feldmann, A., Willinger, W.: There is more to IXPs than meets the eye. ACM SIGCOMM Comput. Commun. Rev. 43(5), 19–28 (2013). https://doi.org/10.1145/2541468.2541473

    Article  Google Scholar 

  28. Cho, S., Fontugne, R., Cho, K., Dainotti, A., Gill, P.: BGP hijacking classification. In: Network Traffic Measurement and Analysis Conference (TMA), pp. 25–32. IEEE (2019). https://doi.org/10.23919/TMA.2019.8784511

  29. Dang, T.K., Mohan, N., Corneo, L., Zavodovski, A., Ott, J., Kangasharju, J.: Cloudy with a chance of short RTTs: analyzing cloud connectivity in the internet. In: Internet Measurement Conference (IMC), pp. 62–79. ACM (2021). https://doi.org/10.1145/3487552.3487854

  30. Del Fiore, J.M., Merindol, P., Persico, V., Pelsser, C., Pescapé, A.: Filtering the noise to reveal inter-domain lies. In: Network Traffic Measurement and Analysis Conference (TMA), pp. 17–24. IEEE (2019). https://doi.org/10.23919/TMA.2019.8784618

  31. Dhamdhere, A., Dovrolis, C.: The internet is flat: modeling the transition from a transit hierarchy to a peering mesh. In: International Conference on emerging Networking EXperiments and Technologies (CoNEXT), pp. 185–198. ACM (2010). https://doi.org/10.1145/1921168.1921196

  32. Dhamdhere, A., Dovrolis, C.: Twelve years in the evolution of the internet ecosystem. IEEE/ACM Trans. Networking 19(5), 1420–1433 (2011). https://doi.org/10.1109/TNET.2011.2119327

    Article  Google Scholar 

  33. Du, B., Testart, C., Fontugne, R., Akiwate, G., Snoeren, A.C., kc claffy: Mind your MANRS: measuring the MANRS ecosystem. In: Internet Measurement Conference (IMC), pp. 716–729. ACM (2022). https://doi.org/10.1145/3517745.3561419

  34. Fontugne, R., Ermoshina, K., Aben, E.: The internet in crimea: a case study on routing interregnum. In: IFIP Networking Conference (Networking), pp. 809–814. IEEE (2020)

    Google Scholar 

  35. Fontugne, R., Pelsser, C., Aben, E., Bush, R.: Pinpointing delay and forwarding anomalies using large-scale traceroute measurements. In: Internet Measurement Conference (IMC), pp. 15–28. ACM (2017). https://doi.org/10.1145/3131365.3131384

  36. Fontugne, R., Shah, A., Aben, E.: The (thin) bridges of AS connectivity: measuring dependency using AS hegemony. In: Beverly, R., Smaragdakis, G., Feldmann, A. (eds.) PAM 2018. LNCS, vol. 10771, pp. 216–227. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-76481-8_16

    Chapter  Google Scholar 

  37. Gamero-Garrido, A.: Transit influence of autonomous systems: country-specific exposure of internet traffic. Ph.D. thesis, University of California, San Diego, USA (2021). https://www.escholarship.org/uc/item/0hg720zn

  38. Gamero-Garrido, A., Carisimo, E., Hao, S., Huffaker, B., Snoeren, A.C., Dainotti, A.: Quantifying nations’ exposure to traffic observation and selective tampering. In: Hohlfeld, O., Moura, G., Pelsser, C. (eds.) PAM 2022. LNCS, vol. 13210, pp. 645–674. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-98785-5_29

    Chapter  Google Scholar 

  39. Giotsas, V., Dietzel, C., Smaragdakis, G., Feldmann, A., Berger, A., Aben, E.: Detecting peering infrastructure outages in the wild. In: Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (SIGCOMM), pp. 446–459. ACM (2017). https://doi.org/10.1145/3098822.3098855

  40. Gregori, E., Improta, A., Lenzini, L., Rossi, L., Sani, L.: On the incompleteness of the as-level graph: a novel methodology for BGP route collector placement. In: Internet Measurement Conference (IMC), pp. 253–264. ACM (2012). https://doi.org/10.1145/2398776.2398803

  41. Henthorn-Iwane, A.: Understanding Internet Exchanges via the DE-CIX Outage, April 2018. https://www.thousandeyes.com/blog/network-monitoring-de-cix-outage

  42. Hyun, Y., Broido, A., kc claffy: On third-party addresses in traceroute paths. In: Passive and Active Network Measurement Workshop (PAM) (2003). https://catalog.caida.org/paper/2003_3rdparty

  43. Hyun, Y., Broido, A., kc claffy: Traceroute and BGP AS Path Incongruities (2003). https://catalog.caida.org/paper/2003_asp

  44. Lodhi, A., Larson, N., Dhamdhere, A., Dovrolis, C., kc claffy: Using PeeringDB to understand the peering ecosystem. ACM SIGCOMM Comput. Commun. Rev. 44(2), 20–27 (2014). https://doi.org/10.1145/2602204.2602208

  45. Mao, Z.M., Rexford, J., Wang, J., Katz, R.H.: Towards an accurate AS-level traceroute tool. In: Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (SIGCOMM), pp. 365–378. ACM (2003). https://doi.org/10.1145/863955.863996

  46. McQuistin, S., Uppu, S.P., Flores, M.: Taming anycast in the wild internet. In: Internet Measurement Conference (IMC), pp. 165–178. ACM (2019). https://doi.org/10.1145/3355369.3355573

  47. Nomikos, G., Dimitropoulos, X.: traIXroute: detecting IXPs in traceroute paths. In: Karagiannis, T., Dimitropoulos, X. (eds.) PAM 2016. LNCS, vol. 9631, pp. 346–358. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-30505-9_26

    Chapter  Google Scholar 

  48. Number Resource Organisation: NRO Extended Allocation and Assignment Reports. https://www.nro.net/about/rirs/statistics/

  49. Prehn, L., Lichtblau, F., Dietzel, C., Feldmann, A.: Peering only? Analyzing the reachability benefits of joining large IXPs today. In: Hohlfeld, O., Moura, G., Pelsser, C. (eds.) PAM 2022. LNCS, vol. 13210, pp. 338–366. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-98785-5_15

    Chapter  Google Scholar 

  50. RIPE Ncc Staff: RIPE atlas: a global internet measurement network. Internet Protocol J. 18(3), 2–26 (2015)

    Google Scholar 

  51. Sermpezis, P., Prehn, L., Kostoglou, S., Flores, M., Vakali, A., Aben, E.: Bias in internet measurement platforms. In: Network Traffic Measurement and Analysis Conference (TMA), pp. 1–10. IEEE (2023). https://doi.org/10.23919/TMA58422.2023.10198985

  52. Tashiro, M.: Atlas traceroute outage inspector. https://github.com/m-appel/atlas-traceroute-outage-inspector

  53. Tashiro, M., Fontugne, R., Fukuda, K.: Accompanying website and data. https://internethealthreport.github.io/ixp-dependency/

  54. Wagner, D., et al.: United we stand: collaborative detection and mitigation of amplification DDoS attacks at scale. In: Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security (CCS), pp. 970–987. ACM (2021). https://doi.org/10.1145/3460120.3485385

  55. Wichtlhuber, M., et al.: IXP Scrubber: learning from blackholing traffic for ml-driven DDoS detection at scale. In: Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (SIGCOMM), pp. 707–722. ACM (2022). https://doi.org/10.1145/3544216.3544268

  56. Winter, P., Padmanabhan, R., King, A., Dainotti, A.: Geo-locating BGP prefixes. In: Network Traffic Measurement and Analysis Conference (TMA), pp. 9–16. IEEE (2019). https://doi.org/10.23919/TMA.2019.8784509

  57. Zhang, Y., et al.: A framework to quantify the pitfalls of using traceroute in AS-level topology measurement. IEEE J. Sel. Areas Commun. 29(9), 1822–1836 (2011). https://doi.org/10.1109/JSAC.2011.111007

    Article  Google Scholar 

Download references

Acknowledgments

We thank the reviewers for their feedback. We would also like to thank Emile Aben from the RIPE NCC for fruitful discussions and CAIDA for giving us access to their dataset.

Author information

Authors and Affiliations

  1. SOKENDAI, Tokyo, Japan

    Malte Tashiro & Kensuke Fukuda

  2. IIJ Research Laboratory, Tokyo, Japan

    Malte Tashiro & Romain Fontugne

  3. NII, Tokyo, Japan

    Kensuke Fukuda

Authors
  1. Malte Tashiro
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Romain Fontugne
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kensuke Fukuda
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Malte Tashiro .

Editor information

Editors and Affiliations

  1. Akamai Technologies, Cambridge, MA, USA

    Philipp Richter

  2. Hasso Plattner Institute, Potsdam, Germany

    Vaibhav Bajpai

  3. Northwestern University, Evanston, IL, USA

    Esteban Carisimo

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Tashiro, M., Fontugne, R., Fukuda, K. (2024). Following the Data Trail: An Analysis of IXP Dependencies. In: Richter, P., Bajpai, V., Carisimo, E. (eds) Passive and Active Measurement. PAM 2024. Lecture Notes in Computer Science, vol 14538. Springer, Cham. https://doi.org/10.1007/978-3-031-56252-5_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-56252-5_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-56251-8

  • Online ISBN: 978-3-031-56252-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation