DRAFT
EE/CS 161

Big Data Networks

9 units (3-0-6)  |  third term
Prerequisites: Linear Algebra ACM/IDS 104 and Introduction to Probability Models ACM/EE/IDS 116 or their equivalents.
Next generation networks will have tens of billions of nodes forming cyber-physical systems and the Internet of Things. A number of fundamental scientific and technological challenges must be overcome to deliver on this vision. This course will focus on (1) How to boost efficiency and reliability in large networks; the role of network coding, distributed storage, and distributed caching; (2) How to manage wireless access on a massive scale; modern random access and topology formation techniques; and (3) New vistas in big data networks, including distributed computing over networks and crowdsourcing. A selected subset of these problems, their mathematical underpinnings, state-of-the-art solutions, and challenges ahead will be covered. Given in alternate years. Not offered 2021-2022.
Instructor: Hassibi

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