Analysis of Communication Networks2023HT
No of lectures
It is expected to have around 9 lectures.
Advanced master students and PhD students.
The course was last given
It is the first time it will be given as a PhD course.
The students will learn mathematical methods for the design of communication networks, using control, optimization, and stochastic network theories.
A basic background on probability theory and stochastic processes.
The first part will cover the fundamentals, the second part will cover more advanced topics, and the third part will be the project by the students.
Optimization formulation of network resource allocation, convergence analysis
of primal and dual algorithms, Delay equations and applications to the study of
congestion control algorithm; Interpretation of network architecture and
algorithms in terms of optimization solution; Game-theoretic interpretation of
optimization formulation and solution
Mathematical tools: Markov chains and discrete-time queueing theory
Statistical multiplexing and large deviations
Scheduling algorithms for switches and wireless networks: Maxweight scheduling, complexity, and distributed randomized algorithms, statistical physics techniques
Other topics as time permits: Throughput scaling laws for wireless networks, Modeling P2P networks, Cloud Computing
The following book will be utilized:
R. Srikant and L. Ying, Communication Networks: An Optimization, Control and Stochastic Networks Perspective, Cambridge University Press, 2014
There will be also research papers to match the interest of the students.
From the content field above, one lecture is expected for each item.
In addition we will have a final day with the presentations of the projects.
A project-based examination where each student can analyze and implement a topic relevant to this book. A presentation is expected along with a written report. There is also a possibility for a written exam or oral examination on the white board. This depends on the amount of students and their preference.
Page responsible: Director of Graduate Studies