Enabling Perception-Driven Optimization in Networking

Abstract

Service providers struggle to catch up with the rapid growth in bandwidth and latency demand of Internet videos and other applications. An essential contributor to this resource contention is the assumption that users are equally sensitive to service quality everywhere, so any low-quality incidents must be avoided. However, this assumption is not true. For example, our work and other parallel efforts have shown that more video users can be served with better quality of experience (QoE) if we embrace the fact that the QoE's sensitivity to video quality varies greatly with the video content. To unleash such benefits, the application systems must be driven by not only system measurement data but also user feedback data that capture users' perceptions of service quality. In this short paper, I will highlight some of our recent efforts toward the efficient collection of user feedback and enabling perception-driven optimization for Internet applications.