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Inferring Cloud Interconnections: Validation, Geolocation, and Routing Behavior

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Passive and Active Measurement (PAM 2021)

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Abstract

Public clouds fundamentally changed the Internet landscape, centralizing traffic generation in a handful of networks. Internet performance, robustness, and public policy analyses struggle to properly reflect this centralization, largely because public collections of BGP and traceroute reveal a small portion of cloud connectivity.

This paper evaluates and improves our ability to infer cloud connectivity, bootstrapping future measurements and analyses that more accurately reflect the cloud-centric Internet. We also provide a technique for identifying the interconnections that clouds use to reach destinations around the world, allowing edge networks and enterprises to understand how clouds reach them via their public WAN. Finally, we present two techniques for geolocating the interconnections between cloud networks at the city level that can inform assessments of their resilience to link failures and help enterprises build multi-cloud applications and services.

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Notes

  1. 1.

    We observed different behavior in February, 2021 (Appendix A).

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Acknowledgments

This work was supported by DARPA CA HR00112020014, NSF OAC-1724853, NSF CNS-1901517, and NSF CNS-1925729.

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Authors and Affiliations

  1. CAIDA, UC San Diego, San Diego, USA

    Alexander Marder & K. C. Claffy

  2. UC San Diego, San Diego, USA

    Alex C. Snoeren

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  1. Alexander Marder
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  2. K. C. Claffy
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  3. Alex C. Snoeren
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Corresponding author

Correspondence to Alexander Marder .

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Editors and Affiliations

  1. Brandenburg University of Technology (BTU), Cottbus, Germany

    Oliver Hohlfeld

  2. Telefonica Research, Barcelona, Spain

    Andra Lutu

  3. Iribe Center, University of Maryland, College Park, MD, USA

    Dave Levin

A Recent GCP Traceroute Behavior

A Recent GCP Traceroute Behavior

Fig. 11.
figure 11

Unlike the traceroute in October, 2020, the traceroute from GCP Los Angeles to UPenn in February, 2021 revealed an internal GCP IP addresses (a). The first responsive hop in the traceroute from Virginia was an address on a UPenn router, but the path contained unresponsive hops until that point (b).

Full size image

We conducted the traceroutes in Sect. 4.1 in October, 2020. Revisiting our examples in February, 2021, we noticed a different behavior. Many paths still do not contain any internal GCP addresses, but the paths no longer appear to start in neighboring networks. As seen in the traceroute path from GCP Los Angeles to UPenn (Fig. 11a), hop #1 is an internal GCP address followed by the interconnection with Internet2 at hop #2 [10], rather than a UPenn address. The first responsive hop in the path from our GCP Virginia VM (Fig. 11b) is the same UPenn address that we previously observed as hop #1 in Sect. 4.1, but hop #1 is now an unresponsive address. This behavior makes interpreting GCP traceroutes more intuitive, as they follow conventional traceroute semantics, but observing GCP internal addresses still appears to depend on the combination of VM region and traceroute destination.

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Marder, A., Claffy, K.C., Snoeren, A.C. (2021). Inferring Cloud Interconnections: Validation, Geolocation, and Routing Behavior. In: Hohlfeld, O., Lutu, A., Levin, D. (eds) Passive and Active Measurement. PAM 2021. Lecture Notes in Computer Science(), vol 12671. Springer, Cham. https://doi.org/10.1007/978-3-030-72582-2_14

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