Taming Anycast in a Wild Internet

Anycast is a popular tool for deploying global, widely available systems, including DNS infrastructure and content delivery networks (CDNs). The optimization of these networks often focuses on the deployment and management of anycast sites. However, such approaches fail to consider one of the primary configurations of a large anycast network: the set of networks that receive anycast announcements at each site (i.e., an announcement configuration). Altering these configurations, even without the deployment of additional sites, can have profound impacts on both anycast site selection and round-trip times. In this study, we explore the operation and optimization of any-cast networks through the lens of deployments that have a large number of upstream service providers. We demonstrate that these many-provider anycast networks exhibit fundamentally different properties when interacting with the Internet, having a greater number of single AS hop paths and reduced dependency on each provider, compared with few-provider networks. We further examine the impact of announcement configuration changes, demonstrating that in nearly 30% of vantage point groups, round-trip time performance can be improved by more than 25%, solely by manipulating which providers receive anycast announcements. Finally, we propose DailyCatch, an empirical measurement methodology for testing and validating announcement configuration changes, and demonstrate its ability to influence user-experienced performance on a global anycast CDN

On the dynamics of interdomain routing in the Internet

The routes used in the Internet's interdomain routing system are a rich information source that could be exploited to answer a wide range of questions.  However, analyzing routes is difficult, because the fundamental object of study is a set of paths. In this dissertation, we present new analysis tools -- metrics and methods -- for analyzing paths, and apply them to study interdomain routing in the Internet over long periods of time. Our contributions are threefold. First, we build on an existing metric (Routing State Distance) to define a new metric 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 paths to each prefix varies at a given timescale. Second, we present PathMiner, a system to extract large scale routing events from background noise and identify the AS (Autonomous System) or AS-link most likely responsible for the event. PathMiner is distinguished from previous work in its ability to identify and analyze large-scale events that may re-occur many times over long timescales. We show that it is scalable, being able to extract significant events from multiple years of routing data at a daily granularity. Finally, we equip Routing State Distance with a new set of tools for identifying and characterizing unusually-routed ASes. At the micro level, we use our tools to identify clusters of ASes that have the most unusual routing at each time. We also show that analysis of individual ASes can expose business and engineering strategies of the organizations owning the ASes.  These strategies are often related to content delivery or service replication. At the macro level, we show that the set of ASes with the most unusual routing defines discernible and interpretable phases of the Internet's evolution. Furthermore, we show that our tools can be used to provide a quantitative measure of the "flattening" of the Internet