Stanford Networking Seminar

12:15PM, Thursday November 17, 2011
Gates 104

Understanding user's perception of performance disruptions at end-hosts

Diana Joumblatt
UPMC Sorbonne Universite

About the talk:
Have you ever had your calls dropped on Skype? Have you ever had a video on YouTube freeze up on you? Network disruptions and dynamic network conditions can adversely impact end-user experience. These issues can frustrate users who are oblivious of the underlying causes, but have to deal with the resulting degradations. In an ideal world, user devices would have the capability to automatically detect and troubleshoot network performance problems or and provide contextual feedback to users when fixes are not available. There is much interest recently in doing automated diagnosis on user laptops and desktops. One interesting aspect of performance diagnosis that has received little attention is the user perspective on performance. In this talk, we present HostView, a data measuring tool that collects network traffic headers and related information at end-hosts. Importantly, Hostview includes mechanisms for users to rate their perceived network conditions, and is a key departure from previous work in the area. We discuss the design tradeoffs in building HostView (overhead, privacy and user annoyance) and the challenges in collecting such data. Then, we present a characterization study of network performance from 40 users across a diversity of networking environments (e.g. home, work, hotel). We also present some results from our attempts to correlate end-user perception (of network conditions) with actual network performance and conclude with some interesting future directions.

About the speaker:
Diana Joumblatt is a Ph.D student in computer science since October 2008 at UPMC in paris. She works in the Networks and Performance Analysis team at LIP6 under the supervision of Renata teixeira. Her research is focused on end-host performance and user perception of network and application performance. She is collaborating with Nina Taft and Jaideep Chandrashekar from technicolor to develop a methodology to automatically detect network performance disruptions as perceived by end-users.