A Framework for Measuring and Predicting the Impact of Routing Changes

Routing dynamics heavily influence Internet data plane performance. Existing studies only narrowly focused on a few destinations and did not consider the predictability of the impact of routing changes on performance metrics such as reachability. In this work, we propose an efficient framework to capture coarse-grained but important performance degradation as a result of BGP routing events using light-weight probing. We deployed our framework across six vantage points for 11 weeks and found that the data plane experienced serious performance degradation in the form of reachability loss and forwarding loops following a significant fraction of updates affecting many destination prefixes and networks across all vantage points studied. Specifically, more than 39% of updates resulted in reachability loss, some lasting for more than 300 seconds, impacting more than 72% of probed prefixes and more than 35% of all the prefixes on the Internet. We identified that more than half of the prefixes have predictable routing behavior. Based on the stationarity of the correlation between routing changes and the data plane performance, we developed a model to accurately predict the severity of the impact due to routing changes. Such a model is directly helpful for making informed decisions for improved routing schemes such as overlay routing and backup path selection.