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.
We are honored to announce that our paper “The Next Generation of BGP Data Collection Platforms” has been awarded the prestigious Best Paper Award at ACM SIGCOMM 2024. This recognition highlights the significance and potential impact of our work on optimizing BGP data collection systems.
For more details and to access the data, visit bgproutes.io.
We thank the SIGCOMM community for this esteemed recognition and look forward to further advancing the field of Internet measurement and routing security.