Characterizing Home User Performance in Access Networks Srikanth Sundaresan (Ph.D. student) Nick Feamster (Assistant Professor) School of Computer Science Joint project with Renata Teixeira at LIP6, Paris

Motivation What affects user performance in home networks? –Geographic location –Choice of ISP –Time of day –User Configuration Understand shared fate among: –users (Do different users experience performance problems at the same time?) –access ISPs (Would getting a second upstream ISP help avoid failures, improve performance, etc.)

Why It Matters Provisioning: Determining where to allocate resources. –US broadband stimulus has $7.2B for buildout of new infrastructure. Where/how to allocate resources? Troubleshooting and Performance –Correlated performance problems may indicate locations of faulty elements –Comparing performance measurements may reveal performance and reliability differences across ISPs

The Data Active network measurements from thousands of home users in France Periodic data collected across multiple ISPs –ping RTTs, loss –Download/upload speed for bulk files Also, topology information from certain ISPs –e.g., mapping of users to DSL access equipment Many Providers/SLAsMany Cities

Data Analysis Statistical analysis –Understand how users differ based on various factors –Model user performance and classify users –Identify outliers and network events Challenges –Quirks in data collection methods –Large variation in data, not much intuition

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