text: The type of business relationships between the Internet autonomous systems (AS) determines the BGP inter-domain routing. Previous works on inferring AS relationships relied on the connectivity information between ASes. In this paper we infer AS relationships by analysing the routing polices of ASes encoded in the BGP attributes Communities and the Locpref. We accumulate BGP data from RouteViews, RIPE RIS and the public Route Servers in August 2010 and February 2011. Based on the routing policies extracted from data of the two BGP attributes, we obtain AS relationships for 39 links in our data, which include all links among the Tier-1 ASes and most links between Tier-1 and Tier-2 ASes. We also reveal a number of special AS relationships, namely the hybrid relationship, the partial-transit relationship, the indirect peering relationship and the backup links. These special relationships are relevant to a better understanding of the Internet routing. Our work provides a profound methodological progress for inferring the AS relationships.
  @cite_9: An understanding of the topological structure of the Internet is needed for quite a number of networking tasks, e. g., making decisions about peering relationships, choice of upstream providers, inter-domain traffic engineering. One essential component of these tasks is the ability to predict routes in the Internet. However, the Internet is composed of a large number of independent autonomous systems (ASes) resulting in complex interactions, and until now no model of the Internet has succeeded in producing predictions of acceptable accuracy.We demonstrate that there are two limitations of prior models: (i) they have all assumed that an Autonomous System (AS) is an atomic structure - it is not, and (ii) models have tended to oversimplify the relationships between ASes. Our approach uses multiple quasi-routers to capture route diversity within the ASes, and is deliberately agnostic regarding the types of relationships between ASes. The resulting model ensures that its routing is consistent with the observed routes. Exploiting a large number of observation points, we show that our model provides accurate predictions for unobserved routes, a first step towards developing structural mod-els of the Internet that enable real applications.
  @cite_2: Routing policies are typically partitioned into a few classes that capture the most common practices in use today[1]. Unfortunately, it is known that the reality of routing policies[2] and peering relationships is far more complex than those few classes[1,3]. We take the next step of searching for the appropriate granularity at which policies should be modeled. For this purpose, we study how and where to configure per-prefix policies in an AS-level model of the Internet, such that the selected paths in the model are consistent with those observed in BGP data from multiple vantage points. By comparing business relationships with per-prefix filters, we investigate the role and limitations of business relationships as a model for policies. We observe that popular locations for filtering correspond to valleys where no path should be propagated according to inferred business relationships. This result reinforces the validity of the valley-free property used for business relationships inference. However, given the sometimes large path diversity ASs have, business relationships do not contain enough information to decide which path will be chosen as the best. To model how individual ASs choose their best paths, we introduce a new abstraction: next-hop atoms. Next-hop atoms capture the different sets of neighboring ASs an AS uses for its best routes. We show that a large fraction of next-hop atoms correspond to per-neighbor path choices. A non-negligible fraction of path choices, however, correspond to hot-potato routing and tie-breaking within the BGP decision process, very detailed aspects of Internet routing.
summary: These works are common in that they mainly relied on a single data source, i.e. the AS connectivity data. Although sophisticated heuristics have been used, the connectivity data itself is inherently limited in providing useful information for inferring AS relationships. Some heuristics can even introduce errors. Inference results produced by different existing algorithms are often inconsistent and sometimes conflict to each other. Two recent works @cite_9 @cite_2 showed that BGP simulations based on these data lead to poor results. In addition, existing algorithms are not capable of discovering any unconventional AS relationships.