AliasCluster: A lightweight approach to interface disambiguation

Internet topologies discovered by standard traceroute-based probing schemes are limited by many factors. One of the main factors is the ambiguity of the returned interfaces, where multiple unique interface IP addresses belong to the same physical router. The unknown assignment of interface IPs to physical routers can result in grossly inflated estimated topologies compared with the true underlying physical infrastructure of the network. The ability to determine which interfaces belong to which router would aid in the ability to accurately reconstruct the underlying topology of the Internet. In this paper, we present ALIASCLUSTER, a lightweight learning-based methodology that disambiguates router aliases using only observed traceroute measurements and requires no additional load on the network. Compared with existing techniques, we find that ALIASCLUSTER can resolve the same number of true router alias pairs with 50% fewer false alarms.