Zhuqi Li will present his Pre FPO "Cross-layer optimization for video delivery on Wireless Networks" on Wednesday, August 10, 2022 at 3pm (EST) via Zoom. Zoom link: [ https://princeton.zoom.us/j/6871275896 | https://princeton.zoom.us/j/6871275896 ] The members of his committee are as follows: Advisor: Kyle Jamieson Readers: Victor Bahl (Microsoft), Amit Levy Examiners: Ravi Netravali, Jennifer Rexford All are welcome to attend. Abstract: A dominating portion of today's wireless network traffic is occupied by video content delivery for both video streaming and live video analytic purposes. The dynamic nature of wireless network presents significant challenges to both applications. On the one hand, the available throughput of the wireless network varies across time due to the change of the wireless channel and competing flows. On the other hand, the endpoints need to decide the video bitrate and routing selection without knowing the future throughput. In this talk, we will introduce three systems that optimize wireless video delivery from physical layer, network layer, and application layer to solve the challenges. We present the design and implementation of the following systems: (1) LAIA: a programmable wireless environment that allows rapid adjustments of the wireless channel to smooth the throughput variation. LAIA uses a large array of inexpensive antenna (LAIA) elements and includes algorithms to configure LAIA elements in real-time. (2) Spider: a multi-hop, millimeter-wave (mmWave) wireless relay network design to maximize end-to-end video analytic accuracy for a large camera cluster. Spider integrates a low-latency Wi-Fi control plane with a mmWave relay data plane, allowing agile re-routing around blockages. Spider proposes a novel video bit-rate allocation algorithm coupled with a scalable routing algorithm that works hand-in-hand toward the application-level objective of maximizing video analytics accuracy, rather than simply maximizing data throughput. (3) Dashlet: a system tailored for the high quality of experience in short video streaming applications. Dashlet proposes a novel out-of-order video chunk pre-buffering mechanism that leverages users’ swipe statistics as well as network throughput history to determine the pre-buffering order and bitrate.