  The discovery of Autonomous Systems (ASes) interconnections and the inference
of their commercial Type-of-Relationships (ToR) has been extensively studied
during the last few years. The main motivation is to accurately calculate
AS-level paths and to provide better topological view of the Internet. An
inherent problem in current algorithms is their extensive use of heuristics.
Such heuristics incur unbounded errors which are spread over all inferred
relationships. We propose a near-deterministic algorithm for solving the ToR
inference problem. Our algorithm uses as input the Internet core, which is a
dense sub-graph of top-level ASes. We test several methods for creating such a
core and demonstrate the robustness of the algorithm to the core's size and
density, the inference period, and errors in the core.
  We evaluate our algorithm using AS-level paths collected from RouteViews BGP
paths and DIMES traceroute measurements. Our proposed algorithm
deterministically infers over 95% of the approximately 58,000 AS topology
links. The inference becomes stable when using a week worth of data and as
little as 20 ASes in the core. The algorithm infers 2-3 times more peer-to-peer
relationships in edges discovered only by DIMES than in RouteViews edges,
validating the DIMES promise to discover periphery AS edges.
