We set out to conduct a social experiment of sorts, to host a hackathon to hack streaming BGP data. We had no idea we would get such an enthusiastic reaction from the community and that we would reach capacity. We were pleasantly surprised at the response to our invitations when 25 experts came to interact with 50 researchers and practitioners (30 of whom were graduate students). We felt honored to have participants from 15 countries around the world and experts from companies such as Cisco, Comcast, Google, Facebook and NTT, who came to share their knowledge and to help guide and assist our challenge teams.

Having so many domain experts from so many institutions and companies with deep technical understanding of the BGP ecosystem together in one room greatly increased the kinetic potential for what we might accomplish over the course of our two days.

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When visualizing the Internet, one can consider several different levels of abstraction, including the Internet Protocal (IP) address, router, and Autonomous System (AS) levels. IP addresses identify interfaces on devices that connect to the Internet. Routers are devices that route traffic by accepting it on one interface and forwarding it out another interface. (Routers may have many interfaces.) An Autonomous Systems (AS) is a set of IP addresses operated under a single administrative umbrella. The three granularities are illustrated below:

Most Internet mapping methods have focused on characterizing and modeling network structure at the level of interconnected Autonomous Systems (ASes). We have developed different ways to annotate ASes, using a variety of available datasets, to support visualizations of AS topology:
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I gave a class lecture at UCSD in January 2016 on visualizing Internet AS topology. I also prepared a supplemental data set to facilitate student exploration and experimentation. Comments and feedback welcome!

As economic pressure imposed by IPv4 address exhaustion has grown, we seek methods to track deployment of IPv6, IPv4’s designated successor. We examine per-country allocation and deployment rates through the lens of the annual “Day in the Life of the Internet” (DITL) snapshots collected at the DNS roots by the DNS Operations, Analysis, and Research Center (DNS-OARC) from 2009 to 2014.

For more details of data sources and analysis, see:
http://www.caida.org/research/policy/dns-country/

We recently released a visualization at http://www.caida.org/research/topology/as_core_network/ that represents our macroscopic snapshots of IPv4 and IPv6 Internet topology samples captured in 2013. The plots illustrate both the extensive geographical scope as well as rich interconnectivity of nodes participating in the global Internet routing system.

IPv4 and IPv6 AS Core Graph, Jan 2013

This AS core visualization addresses one of CAIDA’s topology mapping project goals is to develop techniques to illustrate structural relationships and depict critical components of the Internet infrastructure. These IPv4 and IPv6 graphs show the relative growth of the two Internet topologies, and in particular the steady continued growth of the IPv6 topology. Although both IPv4 and IPv6 topologies experienced a lot of churn, the net change in number of ASes was 3,290 (10.7%) in our IPv4 graph and 495 (25.7%) in our IPv6 graph.

In order to improve our AS Core visualization over previous years, this year we made two major refinements to our graphing methodology, including how we rank individual ASes. First, we now rank ASes based on their transit degree rather then their outdegree. Second, we now infer links across Internet eXchange (IX) point address space, rather than considering the IX itself a node to which various ISPs attach. Details at http://www.caida.org/research/topology/as_core_network/.

[For details on a more sophisticated methodology for ranking AS interconnectivity, based on inferring AS relationships from BGP data, see http://www.caida.org/data/active/as-relationships/.]

[While getting our feet wet with D3 (what a wonderful tool!), we finally tried this analysis tidbit that’s been on our list for a while.]

We recently analyzed the reputation of a country’s Internet (IPv4) addresses by examining the number of blacklisted IPv4 addresses that geolocate to a given country. We compared this indicator with two qualitative measures of each country’s governance. We hypothesized that countries with more transparent, democratic governmental institutions would harbor a smaller fraction of misbehaving (blacklisted) hosts. The available data confirms this hypothesis. A similar correlation exists between perceived corruption and fraction of blacklisted IP addresses.

For more details of data sources and analysis, see:
http://www.caida.org/research/policy/country-level-ip-reputation/

x:Corruption Perceptions Index y:IP population %	x:Democracy Index y:IP population %	x:Democracy Index y:IP infection %

Interactive graph and analysis on the CAIDA website