NeTS: Small: Broadband Service Reliability: Characterization and Improvement

Northwestern University, Evanston IL

Investigators

Abstract

This project studies the reliability of broadband services, explores the relation between reliability and users' quality of experience and investigates edge-based solutions to improve reliability. It develops techniques and investigates metrics to study and characterize reliability problems, and algorithms to diagnose and localize their source, building on existing infrastructure and data collected as part of the Federal Communications Commission's Measuring Broadband America effort. This investigation explores the impact of reliability problems on users' Quality of Experience (QoE), exploring the value of possible proxy metrics for QoE (e.g., session time, traffic demand) and the application of natural experiments and related designs to understand their relationship at scale while controlling for most confounding factors. An understanding of reliability problems, their impact and most common causes should help in the development of readily deployable solutions that might improve service reliability at the network edge. As residential broadband network availability and performance improves, consumers continue to migrate key services such as telephony, television and home monitoring to over-the-top alternatives. This migration comes with rising users' expectations regarding broadband reliability, which is a key factor of consumer experience. Despite the rich history of reliability engineering, researcher have very limited understanding of reliability in the context of broadband, from the most appropriate metrics for characterizing it, to approaches for gathering measurements or assessing their impact on users' quality of experience. When reliability problems appear, troubleshooting them is nearly impossible -- there is no principled approach to determining the source of the problem. The outcome is increased frustration for users, growing management costs for Internet service providers, and, ultimately, underperforming applications. The project enhances undergraduate and graduate teaching, involves undergraduates in research projects, reaches out to industry, provides tools and first-of-its-kind datasets to researchers, and offers a data gathering platform and data for the benefit of Federal and State telecom regulators. The algorithms, tools, techniques and experimental approaches we will develop will help users, operators and policymakers providing a firmer statistical footing for future investment.