Less is More: Optimizing Probe Selection Using Shared Latency Anomalies

2026-02-03

AI Summary

This study addresses the challenge of efficiently identifying shared latency anomalies in residential internet networks, where such anomalies are prevalent yet highly variable in magnitude and duration, and network topology information is typically unavailable. Leveraging high-frequency RTT measurements collected over four months from 99 residential probes in Chicago, the authors propose a topology-agnostic method for detecting shared anomalies. The approach combines change-point detection to identify anomalies with a constrained representative probe sampling algorithm that exploits consistency in anomaly magnitude and duration. Using fewer than half of the available probes, the method captures 95% of the overall anomaly impact, outperforms baseline strategies in covering a greater number of unique anomalies, and significantly improves cost-effectiveness and scalability of monitoring while preserving geographic diversity.

Technology Category

• Data Mining & Knowledge Management: Anomaly/Outlier Detection
• Planning, Routing, and Scheduling: Plan Execution and Monitoring
• Search and Optimization: Distributed Search

Application Category

• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Security and Privacy: Large-scale security measurements
• Web Mining and Content Analysis: Web measurements

Abstract

Latency anomalies, defined as persistent or transient increases in round-trip time (RTT), are common in residential Internet performance. When multiple users observe anomalies to the same destination, this may reflect shared infrastructure, routing behavior, or congestion. Inferring such shared behavior is challenging because anomaly magnitudes vary widely across devices, even within the same ISP and geographic area, and detailed network topology information is often unavailable. We study whether devices experiencing a shared latency anomaly observe similar changes in RTT magnitude using a topology-agnostic approach. Using four months of high-frequency RTT measurements from 99 residential probes in Chicago, we detect shared anomalies and analyze their consistency in amplitude and duration without relying on traceroutes or explicit path information. Building on prior change-point detection techniques, we find that many shared anomalies exhibit similar amplitude across users, particularly within the same ISP. Motivated by this observation, we design a sampling algorithm that reduces redundancy by selecting representative devices under user-defined constraints. Our approach captures 95 percent of aggregate anomaly impact using fewer than half of the deployed probes. Compared to two baselines, it identifies significantly more unique anomalies at comparable coverage levels. We further show that geographic diversity remains important when selecting probes within a single ISP, even at city scale. Overall, our results demonstrate that anomaly amplitude and duration provide effective topology-independent signals for scalable monitoring, troubleshooting, and cost-efficient sampling in residential Internet measurement.

Problem

• latency anomalies
• probe selection
• residential Internet
• shared infrastructure
• RTT measurement

Innovation

• shared latency anomalies
• topology-agnostic
• probe selection
• change-point detection
• residential Internet measurement