Course Description

This course is an advanced research seminar for graduate students. The objective is to study and learn the most recent advances in models and algorithmic developments for analysis and optimization of large scale distributed systems. The course is mainly motivated by the emergence of large scale networks, characterized by the lack of a centralized coordinator or centralized access to information, and time-varying system characteristics such as connectivity. The purpose of this course is to study such systems by exploring the interplay of optimization theory, game theory, dynamical systems, and to some extent graph theory. The topics to be covered include models and algorithms for distributed rate allocation and congestion control over communication networks (such as the internet), distributed coordination algorithms (such as consensus and gossip) over networks with applications to multi-vehicle systems and sensor networks, coverage problems, and distributed control, as well as quantization and synchronization phenomena in engineered systems.


Credit: 4 hours Meeting: MW 3-4:40 pm Location: MEB 256 Office Hours: M 2-3 TB 211


Prerequisites: Basic background in Multivariate Calculus, Linear Algebra, and Optimization or instructor's permission.


Requirements: This course requires a lot of independent work. There are a few traditional lectures. Students are expected to critically read and analyze research papers across various disciplines.


Assignments: Everyone participating in the course shall read all the selected papers. Each student will present several papers in a form of group lectures. Grades will be based on the quality of the presentations and overall participation in the class discussions (60% presentation 40% participation). Some special projects may be assigned if necessary.


Textbook: None. The course syllabus with tentative list of selected papers for readings can be downloaded HERE (MS doc).


Readings: