IEEE/ACM Transactions on Networking (TON)
BGP routing stability of popular destinations
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
BGP routing dynamics revisited
ACM SIGCOMM Computer Communication Review
In search for an appropriate granularity to model routing policies
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Ten years in the evolution of the internet ecosystem
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement
Path-vector routing stability analysis
ACM SIGMETRICS Performance Evaluation Review
BGP churn evolution: a perspective from the core
IEEE/ACM Transactions on Networking (TON)
Inferring visibility: who's (not) talking to whom?
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
Routing state distance: a path-based metric for network analysis
Proceedings of the 2012 ACM conference on Internet measurement conference
Hi-index | 0.00 |
The dynamics of interdomain routing have traditionally been studied through the analysis of BGP update traffic. However, such studies tend to focus on the volume of BGP updates rather than their effects, and tend to be local rather than global in scope. Studying the global state of the Internet routing system over time requires the development of new methods, which we do in this paper. We define a new metric, MRSD, that allows us to measure the similarity between two prefixes with respect to the state of the global routing system. Applying this metric over time yields a measure of how the set of total paths to each prefix varies at a given timescale. We implement this analysis method in a MapReduce framework and apply it to a dataset of more than 1TB, collected daily over 3 distinct years and monthly over 8 years. We show that this analysis method can uncover interesting aspects of how Internet routing has changed over time. We show that on any given day, approximately 1% of the next-hop decisions made in the Internet change, and this property has been remarkably constant over time; the corresponding amount of change in one month is 10% and in two years is 50%. Digging deeper, we can decompose next-hop decision changes into two classes: churn, and structural (persistent) change. We show that structural change shows a strong 7-day periodicity and that it represents approximately 2/3 of the total amount of changes.