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MAnycast² Anycast Census Data Repository

This repository contains the dataset of the Anycast Census (detected /24 Anycast Prefixes), discovered using MAnycast² and validated with iGreedy.

Introduction

  • Since its introduction in 1993, anycast addressing RFC1546 has become a fundamental mechanism to increase the resilience and performance of Internet services.
  • Anycast has been adopted by several cloud providers, Content Delivery Networks (CDNs), and DDoS protection services, among others.
  • In a collaboration between UTwente, CAIDA, and SIDN, we proposed a new measurement and inference technique, called MAnycast², which relies on an anycast testbed to efficiently detect anycast prefixes.
  • The idea behind MAnycast² is quite simple: We send ICMP echo-requests with our anycast IP address as a source, from all of the anycast nodes in our testbed. The traffic of the ICMP echo-responses to the anycast IP will be then routed back on a single node, if the target is unicast and on multiple nodes, in case the target is anycast.

Paper

The paper descibing MAnycast² is available here PDF. Reference:

@inproceedings{10.1145/3419394.3423646,
      author = {Sommese, Raffaele and Bertholdo, Leandro and Akiwate, Gautam and Jonker, Mattijs and van Rijswijk-Deij, Roland and Dainotti, Alberto and Claffy, KC and Sperotto, Anna},
      title = {MAnycast2: Using Anycast to Measure Anycast},
      year = {2020},
      isbn = {9781450381383},
      publisher = {Association for Computing Machinery},
      address = {New York, NY, USA},
      url = {https://doi.org/10.1145/3419394.3423646},
      doi = {10.1145/3419394.3423646},
      booktitle = {Proceedings of the ACM Internet Measurement Conference},
      pages = {456–463},
      numpages = {8},
      location = {Virtual Event, USA},
      series = {IMC '20}
}

Dataset

We improved our census by deploying MAnycast² on the SIDN Anycast network (20 nodes, geographical distributed). In the new census of Jan 2021, we solved most of the incorrect classification cases described in the paper (route flips, preferred routes with large operators).

We integrated iGreedy as the second step of validation (and use it for enumeration and geolocation). We performed iGreedy measurements with a set of 500 Ripe ATLAS probes equally geographically distributed (200 Km of minimum distances between them)

Date Dataset # /24 Anycast
Jan 2021 Jan 2021 9999
Apr 2021 Apr 2021 8803
Jul 2021 Jul 2021 9567
Oct 2021 Oct 2021 9208
Jan 2022 Jan 2022 8262
Nov 2023 Nov 2023 12071

Disclaimer

The Nov 2023 dataset contains only the anycast /24 prefixes (and not their enumeration and geolocation). The second step validation was performed using the Ark platform instead of Ripe ATLAS.

Terms of Use

If you make use of any of the open access data from the MAnycast² project, you must acknowledge use of this data by including the following attribution in any document, web page or other communication:

"The research leading to these results was made possible by MAnycast²
(https://github.com/ut-dacs/Anycast-Census/), a joint project of the University of
Twente, SIDN, and CAIDA."

Furthermore, if you use open access data from the MAnycast² project for research that is published in a scientific paper, poster or other peer reviewed content, you must cite the following paper as describing the method through which the data has been collected:

Raffaele Sommese, Leandro Bertholdo, Gautam Akiwate, Mattijs Jonker, Roland van Rijswijk-Deij, Alberto Dainotti, KC Claffy, and Anna Sperotto. 2020. MAnycast2: Using Anycast to Measure Anycast. In Proceedings of the ACM Internet Measurement Conference (IMC '20). Association for Computing Machinery, New York, NY, USA, 456–463. DOI:https://doi.org/10.1145/3419394.3423646

We keep track of research papers that use data from MAnycast² on this website, and would appreciate it if you can notify us of any publications in which you use our datasets. Please contact r.sommese@utwente.nl and a.sperotto@utwente.nl, and send us the citation of you paper.