Xiaoqi (Danny) Chen will present his FPO "Designing Compact Data Structures for Network Measurement and Control" on Wednesday, October 4, 2023 at 2pm in Friend Center 125 (and Zoom). Zoom link: [ https://princeton.zoom.us/j/96617518355 | https://princeton.zoom.us/j/96617518355 ] The members of his committee are as follows: Examiners: Jennifer Rexford (adviser), David Walker, and Maria Apostolaki Readers: Mark Braverman and Minlan Yu (Harvard University) Talk abstract follows below. All are welcome to join. Abstract: This dissertation explores the implementation of network measurement and closed-loop control in the data plane of high-speed programmable switches. After discussing the algorithmic constraints imposed by the switch pipeline architecture, primarily stemming from the requirement of high-speed processing, we share our experience in tailoring algorithms for the data plane. Initially, we focus on efficient measurement algorithms, and present two works for detecting heavy hitters and executing multiple distinct-count queries; both require designing novel approximate data structures to meet the tight memory access constraints. Subsequently, we pivot towards using real-time, closed-loop control in the data plane for performance optimization, and present two works for mitigating microbursts and enforcing fair bandwidth limits; both require approximated computation and exploit the sub-millisecond reaction latency unattainable through conventional control planes. We hope by sharing our experience and techniques, which are widely applicable to various algorithms and other data-plane hardware targets, we can lay the foundation for future innovations in the field of network programming for researchers and practitioners alike.