Introduction to Network Science

Student/Faculty's Expectations on Teaching and Learning

Instructor: John C.S. Lui

This is an introductory course on "Network Science", in particular, it is about the theories, algorithms as well as system issues for large scale networks such as online social networks, Internet, geo-distributed data center networks (DCNs). In this course, we cover fundamental principles and theories for such large scale networks. Furthermore, how one can use these basic analytical tools and algorithms to understand the structures and dynamic of such networks.

Note that this course is "conceptual" in nature. Students need to spend the time to attend the lectures , read the book(s) or papers, do the assignments and finish the project so to understand and keep pace with the class.

Teaching Assistants

Textbook:

Course Grades:

Policy: Late homework or programming assignments will NOT be considered.


FINAL EXAMINATION : Date April 21, 7:00 pm to 9:00 pm, 2016. YIA Room 401 !!!!!! Final Examination :

Please note that the final examination is NOT an open-book exam. You are allowed to bring in one piece of A4 paper (or 2-pages) of ``cheat sheet'' . Topics to be covered in the final exam are:


Tentative Outline for the Course:


Lecture Notes: (Password Protected)

Administrative matter

Introduction to Network Science
Introduction to Technological Networks
Introduction to Social Networks
Introduction to Networks of Information
Mathematics of Networks
Performance Measures and Metrics
Large-scale Structure of Networks
Fundamental Network Algorithms
Matrix Algorithms and Graph Partitioning
Random Networks
Random Networks with General Degree Distributions
Theory of Network Formation
Network Models of Small-world and Exponential Random Graphs (*****)
Percolation and Network Resilience (*****)
Epidemics on Networks (*****)
Dynamical Systems on Networks (*****)
Network Search (*****)

Introduction to Theory of Submodularity
Calculation of Group Closeness Centrality
Analyzing Competitive Influence Maximization Problems with Partial Information
Boosting Information Spread: An Algorithmic Approach

Homework (Password Protected) Submission: Please submit your homework in class
Homework 1 (Deadline: Feb 18, 2016. 7:00 pm, in the lecture period) Solution to Homework 1

Homework 2 (Deadline: March 10 , 2016. 7:00 pm, in the lecture period) Solution to Homework 2

Project (Password Protected) Submission: Please submit your programming project by May 3rd, 2016.
Programming Project (Graph Data for 964 nodes and 3,000 undirected edges)

References: