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2017　Advanced Topics in Computing BO

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Academic unit or major
School of Computing
Instructor(s)
Blaszczyszyn Bartlomiej 
Class Format
Lecture     
Media-enhanced courses
Day/Period(Room No.)
Tue5-6(W831)  Fri5-6(W831)  
Group
-
Course number
XCO.T499
Credits
2
Academic year
2017
Offered quarter
3-4Q
Syllabus updated
2017/10/2
Lecture notes updated
-
Language used
English
Access Index

Course description and aims

This course provides lectures on stat-of-the-art topics by faculty members invited from overseas universities.

Introduction to Spatial Stochastic Modeling: Random Graphs, Point Processes and Stochastic Geometry

The goal of the course is to provide quick access to some mathematical tools useful in the modeling and analysis of modern communication networks, including social, transportation, wireless networks, etc. Historically, these tools might have been developed and belong to different theories, as the theory of percolation, random graphs, point processes and stochastic geometry. Here, we present them in one course that gives us an opportunity to observe some similarities and even some fundamental relations between apparently different concepts, e.g. formalization of the notion of the typical node in random graphs via unimodularity and the mass transport principle for point processes, or a similar role the Galton-Watson tree and Poisson point process are playing in the two aforementioned settings.

Student learning outcomes

Students should be able to discuss on the topics.

Keywords

state-of-the-art topics in information science and technology

Competencies that will be developed

✔ Specialist skills ✔ Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

Specified in the class

Course schedule/Required learning

  Course schedule Required learning
Class 1 Bond Percolation Model Specified in the class
Class 2 Galton-Watson Tree Specified in the class
Class 3 Erdos-Renyi Graph I - Emergence of the Giant Component Specified in the class
Class 4 Configuration Model Specified in the class
Class 5 Unimodular Graphs Specified in the class
Class 6 Erdos-Renyi Graph II - Emergence of the Connectivity Specified in the class
Class 7 Poisson Point Process Specified in the class
Class 8 Palm Theory Specified in the class
Class 9 Hard Core Models Specified in the class
Class 10 Stationary Framework for Point Processes and Mass Transport Principle Specified in the class
Class 11 Stationary Voronoi Tessellation Specified in the class
Class 12 Ergodicity and Point-shift Invariance Specified in the class
Class 13 Random Closed Sets Specified in the class
Class 14 Boolean Model I - Coverage Properties Specified in the class
Class 15 Boolean Model II - Connectivity (Continuum Percolation) Specified in the class

Textbook(s)

None. The notes will be sent after each lesson to students who follow the lecture.

Reference books, course materials, etc.

1. M. Draief & L. Massoulie. Epidemics and Rumours in Complex Networks. Cambridge, 2010.
2. R. van der Hofstad. Random Graphs and Complex Networks. Cambridge, 2017 (available also on
http://www.win.tue.nl/~rhofstad/publications.html).
3. D. J. Daley & D. Vere-Jones. An Introduction to the Theory of Point Processes, Volume II: General Theory and Structure.
Springer, 2008.
4. S. N. Chiu, D. Stoyan, W. S. Kendall & J. Mecke. Stochastic Geometry and its Applications. Wiley, 2013.
5. G. R. Grimmett. Percolation. Springer, 1999.

Assessment criteria and methods

A take-home exam at the end of the course

Related courses

  • XCO.T496 ： Advanced Topics in Computing AE
  • XCO.T497 ： Advanced Topics in Computing AO
  • XCO.T498 ： Advanced Topics in Computing BE

Prerequisites (i.e., required knowledge, skills, courses, etc.)

Specified in the class

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