The goal of this course is to get students familiar with architectures of Fog/Edge/Cloud computing systems to support Internet-of-Things applications, understand the challenges and open problems researchers and developers are currently facing in building these systems, and gain essential background knowledge on tackling those challenges. This course serves as an introductory PG course to state-of-the-art research problems on improving efficiency, robustness, privacy, and scalability of modern IoT computing systems, and novel techniques using information/coding theory, optimization, and cryptography to solve the problems.
Course materials:
Topics that will be covered include coded storage/caching, coded computing to reduce tail latency and bandwidth consumption, security and privacy in distributed machine learning and federated learning, mobile edge computing and computation offloading, and blockchain systems.
Pre-requisite:
Prior knowledge on probability is needed (or can be obtained along the course). Backgrounds on information/coding theory, learning theory and optimization are preferred.
Grading:
Class participation and notes scribing - 10%
In-class presentation - 20%
Course project
Project proposal - 10%
Mid-term report & presentation - 30%
Final report & presentation - 30%
Class schedule
Lec. #
Date
Topics
References
1
Feb. 1
Introduction to IoT infrastructures and applications