Network Optimization and Learning

Catalog description

This course targets a fundamental understanding of communication networks as well as their principled network algorithm design. We explore methods for analyzing the performance of communication networks and principled network algorithm design. In particular, we first present an overview of basic convex optimization and its application for Internet congestion control and routing design. Then, we present a stochastic network optimization framework and its application for scheduling design. Finally, we delve into a multi-agent learning framework for emerging network applications such as networking for virtual/augmented reality. By the end of this course, students will have acquired a solid theoretical foundation at the intersection of networking, optimization, and machine learning for both traditional communication networks and emerging network applications.