Complex Networks: Modeling, Dynamics and Control



Lecturer: Prof Guanrong (Ron) Chen



Offered:  SemB in 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016


Course Aims and Objectives: 


This course will study the emerging topic of complex networks, especially those regarded as evolving and dynamical,

i.e. huge and diverse in many respects. Complex networks such as the Internet, WWW, transportation networks,

power grids, biological neural networks, and scientific cooperation networks of all kinds provide challenges for

future technological development. In particular, advanced societies have become dependent on large infrastructural

networks to an extent beyond our capability to plan (modeling) and to operate (control). The recent spate of

collapses in power grids and ongoing virus attacks on the Internet illustrate the need for knowledge about

modeling, analysis of behaviors, optimized planning and performance control in such networks. For advancement

of techniques, it has become clear that more fundamental knowledge will be needed in an engineering context

about how dynamical networks emerge, behave, adapt, self-organize, evolve, and how they can be controlled.

The aim is to present the status of these topics and some basic techniques of various complex dynamical networks.


Intended Learning Outcomes

Upon completion of this course, the students will be able to

  • apply basic knowledge of graph theory to various engineering problems

  • apply basic concepts to build representative network models

  • analyze the effects of network structures on dynamical behaviors

  • determine local and global network stability, synchronizability and controllability

  • develop efficient and/or optimized algorithms for specific tasks

  • analyze data flows and network topological effects

  • employ the learned techniques to solve some practical problems

Units:  3 

Level:  P6 

Medium of Instruction: English




Graph Theory Fundamentals


Basic concepts, Eulerian graphs, Hamiltonian graphs, applications (minimum connector problem, Chinese

postman problem, shortest path problem), directed networks

Network Structures and Properties


Recent advances in scientific literature including the complexity of models, degree distributions, random graphs,

small-world characteristics, scale-free features, nevigability, community structures, and network modeling


Network Dynamics


Network dynamical behaviors; stability and synchronization; community formation; human opinion dynamics;

network evolution and control

Network Performance


Internet topology; network evolution; information flows; epidemics spreading; cascade failures; network

search; network stability


Network Synchronization and Control


Network synchronization phenomena and criteria; network games; network stabilization and pinning control;

data traffic congestion control; design and optimization of network topologies


Potential Applications


Internet; power grids; transportation; human behavioral dynamics; physical, economic and social networks


Teaching Methods:

Lecturing is the core of teaching. Lectures may involve presentations by some students and invited speakers.

Reading materials will be assigned. One homework assignment will be given in the first few weeks

followed by a one-month computer project assignment. 


Teaching Pattern:
Duration of course: 1 semester
Offered in: Semester B of 2007, 08, 09, 10, 11, 12, 13, 14, 15, 16
Suggested lecture/tutorial/laboratory: Mixed 
Total Hours:  Lectures: 39 hours


Assessment Pattern:  

40% Course Work (homework 10%; projects 30%); 60% Final Exam (closed-book exam)

Examination duration:  2 hours, at the end of the semester



For a student to pass the course, according to the university guidelines, at least 35% of the maximum mark

for the course work and also 35% of the maximum mark for the final exam must both be obtained.


Pre-requisites: Nil 

Pre-cursor: Nil

Equivalent Courses: Nil 


Use Lecture Notes

References (recommended but not required)

[1] G. Chen, X. Wang and X. Li, Introduction to Complex Networks: Models, Structures and Dynamics,

       Higher Education Press, Beijing, 2012.

[2] X. Wang, X. Li and G. Chen, Network Science: An Introduction (in Chinese),

        Higher Education Press, Beijing, 2012.