Rediscovering Recurring Routing Results

2025-10-23

AI Summary

Frequent Internet routing changes degrade performance—increasing latency, operational costs, and data sovereignty risks while reducing throughput. To address this, we propose Fenrir, the first system enabling fine-grained, multi-hop routing change awareness. Methodologically, Fenrir (1) formalizes and models routing “patterns” and introduces a similarity metric grounded in path semantics and topological structure; and (2) integrates BGP announcements, active probing, and weighted data cleaning to construct a quantifiable, reproducible routing change analysis framework. Evaluated across five representative scenarios—including root DNS anycast, multi-homed enterprise networks, and large-scale website placement—Fenrir significantly improves routing anomaly detection accuracy and historical pattern recognition. It provides a general-purpose analytical tool for traffic engineering evaluation and root-cause attribution of external routing changes.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Data Mining & Knowledge Management: Anomaly/Outlier Detection
• Knowledge Representation and Reasoning: Action, Change, and Causality

Application Category

• Responsible Web: Measurement, analysis, and circumvention of Web censorship
• Web Mining and Content Analysis: Models for Web evolution
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Routing is central to networking performance, including: (1) latency in anycast services and websites served from multiple locations,(2) networking expenses and throughput in multi-homed enterprises, (3) the ability to keep traffic domestic when considering data sovereignty. However, understanding and managing how routing affects these services is challenging. Operators use Traffic Engineering (TE) with BGP to optimize network performance, but what they get is the result of all BGP policies throughout the Internet, not just their local choices. Our paper proposes Fenrir, a new system to rediscover recurring routing results. Fenrir can discover changes in network routing, even when it happens multiple hops away from the observer. Fenrir also provides new methods to quantify the degree of routing change, and to identify routing "modes" that may reappear. Second, we show that Fenrir can be applied to many different problems: we use five instances of three different types of systems to illustrate the generalization: anycast catchments showing in a root DNS service, route optimization for two multi-homed enterprises, and website selection for two of the top-10 web services. Each type requires different types of active measurements, data cleaning and weighting. We demonstrate Fenrir's methods of detecting and quantifying change are helpful because they all face similar operational questions: How much effect did traffic engineering have? Did a third-party change alter my routing? In either case, is the current routing new, or is it like a routing mode I saw before?

Problem

• Detecting routing changes affecting network performance
• Quantifying routing change impact on diverse services
• Identifying recurring routing modes for operational decisions

Innovation

• Fenrir system detects distant network routing changes
• Quantifies routing change degree and identifies recurring modes
• Applies to multiple systems with tailored active measurements