Abstract: Video traffic already represents a significant fraction of today’s traffic and is projected to exceed 90% in the next five years. In parallel, user expectations for a high quality viewing experience are continuously increasing. To address this challenge, we argue for a coordinated video control plane architecture that takes actions to optimize video quality (e.g., switch the bitrate and CDN) based on a global real-time view of client conditions. Using trace driven analysis and experimental results, we show that such a control plane can significantly improve the viewing experience, even in the presence of rapid changes in the CDN and network delivery quality.
CV: Ion Stoica is a Professor in the EECS Department at University of California at Berkeley. He received his PhD from Carnegie Mellon University in 2000. He does research on cloud computing and networked computer systems. Past work includes the Dynamic Packet State (DPS), Chord DHT, Internet Indirection Infrastructure (i3), declarative networks, replay-debugging, and multi-layer tracing in distributed systems. His current research focuses on resource management and scheduling for data centers, cluster computing frameworks, and network architectures. He is an ACM Fellow and has received numerous awards, including the SIGCOMM Test of Time Award (2011), and the ACM doctoral dissertation award (2001). In 2006, he co-founded Conviva, a startup to commercialize technologies for large scale video distribution, and in 2013, he co-founded Databricks as startup to commercialize technologies for Big Data processing.