BGP data collection platforms as currently architected face fundamental challenges that threaten their long-term sustainability. Inspired by recent work, we analyze, prototype, and evaluate a new optimization paradigm for BGP collection. Our system scales data collection with two components: analyzing redundancy between BGP updates and using it to optimize sampling of the incoming streams of BGP data. An appropriate definition of redundancy across updates depends on the analysis objective. Our contributions include: a survey, measurements, and simulations to demonstrate the limitations of current systems; a general framework and algorithms to assess and remove redundancy in BGP observations; and quantitative analysis of the benefit of our approach in terms of accuracy and coverage for several canonical BGP routing analyses such as hijack detection and topology mapping. Finally, we implement and deploy a new BGP peering collection system that automates peering expansion using our redundancy analytics, which provides a path forward for more thorough evaluation of this approach.

Dramatic growth in Internet connectivity poses a challenge for the resource-constrained data collection efforts that support scientific and operational analysis of interdomain routing. Inspired by tradeoffs made in other disciplines, we explore a fundamental reconceptualization to how we design public BGP data collection architectures: an overshoot-and-discard approach that can accommodate an order of magnitude increase in vantage points by discarding redundant data shortly after its collection. As defining redundant depends on the context, we design algorithms that filter redundant updates without optimizing for one objective, and evaluate our approach in terms of detecting two noteworthy phenomena using BGP data: AS-topology mapping and hijacks. Our approach can generalize to other types of Internet data (e.g., traceroute, traffic). We offer this study as a first step to a potentially new area of Internet measurement research.

Scrutinizing BGP routes is part of the everyday tasks that network operators and researchers conduct to monitor their networks and measure Internet routing. This task is facilitated by the expansion of routing information services such as RIPE RIS [2] and Route-Views [3] that collect BGP routes from an increasing number of Vantage Points (VPs). Unfortunately, while more data is often beneficial, in the case of BGP, it involves downloading and processing large volumes of route updates that exhibit a high level of redundancy. Today with more than one billion route updates collected every day, users often have no other option than to focus on a subset of the VP. Because of the highly skewed location of the VP, randomly selecting them may result in a lot of missing information.

With the growth of demands for quasi-instantaneous communication services such as real-time video streaming, cloud gaming, and industry 4.0 applications, multi-constraint Traffic Engineering (TE) becomes increasingly important. While legacy TE management planes have proven laborious to deploy, Segment Routing (SR) drastically eases the deployment of TE paths and thus became the most appropriate technology for many operators. The flexibility of SR sparked demands in ways to compute more elaborate paths. In particular, there exists a clear need in computing and deploying Delay-Constrained Least-Cost paths (DCLC) for real-time applications requiring both low delay and high bandwidth routes. However, most current DCLC solutions are heuristics not specifically tailored for SR. In this work, we leverage both inherent limitations in the accuracy of delay measurements and an operational constraint added by SR. We include these characteristics in the design of BEST2COP, an exact but efficient ECMP-aware algorithm that natively solves DCLC in SR domains. Through an extensive performance evaluation, we first show that BEST2COP scales well even in large random networks. In real networks having up to thousands of destinations, our algorithm returns all DCLC solutions encoded as SR paths in way less than a second.