Internet eXchange Points (IXP) are critical components of the Internet infrastructure that affect its performance, evolution, security and economics. In this work, we introduce techniques to augment the well-known traceroute tool with the capability of identifying if and where exactly IXPs are crossed in endto- end paths. Knowing this information can help end-users have more transparency over how their traffic flows in the Internet. Our tool, called traIXroute, exploits data from the PeeringDB (PDB) and the Packet Clearing House (PCH) about IXP IP addresses of BGP routers, IXP members, and IXP prefixes. We show that the used data are both rich, i.e., we find 12,716 IP addresses of BGP routers in 460 IXPs, and mostly accurate, i.e., our validation shows 92-93 accuracy. In addition, 78.2 of the detected IXPs in our data are based on multiple diverse evidence and therefore help have higher confidence on the detected IXPs than when relying solely on IXP prefixes. To demonstrate the utility of our tool, we use it to show that one out of five paths in our data cross an IXP and that paths do not normally cross more than a single IXP, as it is expected based on the valley-free model about Internet policies. Furthermore, although the top IXPs both in terms of paths and members are located in Europe, US IXPs attract many more paths than their number of members indicates.
Recently, Giotsas . @cite_10 introduced techniques to identify the physical facility where ASes interconnect using targeted traceroute measurements and a combination of publicly available facility and IXP based information.
@cite_10
2530522083
Annotating Internet interconnections with robust physical coordinates at the level of a building facilitates network management including interdomain troubleshooting, but also has practical value for helping to locate points of attacks, congestion, or instability on the Internet. But, like most other aspects of Internet interconnection, its geophysical locus is generally not public; the facility used for a given link must be inferred to construct a macroscopic map of peering. We develop a methodology, called constrained facility search, to infer the physical interconnection facility where an interconnection occurs among all possible candidates. We rely on publicly available data about the presence of networks at different facilities, and execute traceroute measurements from more than 8,500 available measurement servers scattered around the world to identify the technical approach used to establish an interconnection. A key insight of our method is that inference of the technical approach for an interconnection sufficiently constrains the number of candidate facilities such that it is often possible to identify the specific facility where a given interconnection occurs. Validation via private communication with operators confirms the accuracy of our method, which outperforms heuristics based on naming schemes and IP geolocation. Our study also reveals the multiple roles that routers play at interconnection facilities; in many cases the same router implements both private interconnections and public peerings, in some cases via multiple Internet exchange points. Our study also sheds light on peering engineering strategies used by different types of networks around the globe.