Giotsas, Vasileios and Koch, Thomas and Fazzion, Elverton and Cunha, Ítalo and Calder, Matt and Madhyastha, Harsha V. and Katz-Bassett, Ethan (2020) Reduce, Reuse, Recycle:Repurposing Existing Measurements to Identify Stale Traceroutes. In: IMC 2020 - Proceedings of the 2020 ACM Internet Measurement Conference. Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC . Association for Computing Machinery (ACM), USA, pp. 247-265. ISBN 9781450381383
Full text not available from this repository.Abstract
Many systems rely on traceroutes to monitor or characterize the Internet. The quality of the systems' inferences depends on the completeness and freshness of the traceroutes, but the refreshing of traceroutes is constrained by limited resources at vantage points. Previous approaches predict which traceroutes are likely out-of-date in order to allocate measurements, or monitor BGP feeds for changes that overlap traceroutes. Both approaches miss many path changes for reasons including the difficulty in predicting changes and the coarse granularity of BGP paths. This paper presents techniques to identify out-of-date traceroutes without issuing any measurements, even if a change is not visible at BGP granularity. We base our techniques on two observations. First, although BGP updates encode routes at AS granularity, routers issue updates when they change intra-domain routes or peering points within the same AS path. Second, route changes correlate across paths, and many publicly available traceroutes exist. Our techniques maintain an atlas of traceroutes by monitoring BGP updates and publicly available traceroutes for signals to mark overlapping atlas traceroutes as stale. We focus our analysis of traceroute path changes at the granularity of border router IPs which provides an abstraction finer than AS- or PoP-level but is not affected by the periodicity of intra-domain load balancers. Our evaluation indicates that 80% of the traceroutes that our techniques signal as stale have indeed changed, even though the AS hops remained the same. Our techniques combine to identify 79% of all border IP changes, without issuing a single online measurement.