186.812 Networks: Design and Analysis
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2019S, VU, 2.0h, 3.0EC

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise

Aim of course

Networks are apparent in our daily lives. Typical examples of networks are: electrical and power networks, telephone or Internet data networks, traffic networks (highways, rail networks, airline service networks), manufacturing and distribution networks, or even social networks.


In this course, we are going to study two main aspects of networks:

1) Design of optimal network topologies. We will study two representative problems from this well-established research field using methods of complexity, algorithms and operations research.

2) Analysis of social networks. The growing public excitement by the global ``connectivity'' of the modern society has motivated scientists from multiple scientific disciplines (computer science, applied mathematics, economy and sociology) to develop this new interdisciplinary research field. We will study several graph-theoretical concept of social networks, their complexity and algorithmic approaches for their analysis.


Learning Objectives

This course should help graduate students to: a) understand information about networks, and b) develop models and algorithms to design, manage and analyse networks.

In particular the main aims of the course are to:
- provide the knowledge of the fundamental concepts of networks
- learn skills in modeling optimization or analysis tasks on networks
- learn skills in developing algorithmic techniques. This includes in particular the development of: 1) combinatorial algorithms (for polynomially solvable cases), 2) polynomial time heuristics with a constant approximation ratio and 3) exact algorithms applied to the corresponding mixed integer programming models.

Subject of course

1) Network design
- Two fundamental network design problems: Steiner trees and Steiner networks (aka survivable network design problems). Complexity, combinatorial algorithms with constant approximation ratio, primal-dual algorithms, integer linear programming (ILP) models and branch-and-cut

2) Analysis of social networks
- Strong and week ties, betweenness measures, graph partitioning
- Networks in their surrounding contexts: homophily, affiliation
- Positive and negative relationships: structural balance, weaker form of structural balance, generalization
- Cascading behavior in networks: diffusion, cascades and clusters. Knowledge, threshold and collective action. The cascade capacity.
- Basics of Game Theory and its application to Networks
- Influence Maximization in Networks
- Link Analysis and Web Search




In the practical assignments, students will develop algorithms for solving related problems using standard network data sets available in the literature.

Additional information

Total: 3 ECTS points (i.e, 75 hours):
25    hours: Lectures
10    hours: Student Presentations
20    hours: Preparing the programming exercise and homework assignments
19.0 hours: Preparing the written exam
1.0 hours: Written Exam

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Mon13:00 - 15:0004.03.2019 - 24.06.2019Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon13:00 - 15:0003.06.2019Seminarraum FAV 01 B (Seminarraum 187/2) Vorlesung
Networks: Design and Analysis - Single appointments
DayDateTimeLocationDescription
Mon04.03.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon11.03.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon18.03.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon25.03.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon01.04.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon08.04.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon15.04.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon22.04.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon29.04.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon06.05.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon13.05.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon20.05.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon27.05.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon03.06.201913:00 - 15:00Seminarraum FAV 01 B (Seminarraum 187/2) Vorlesung
Mon10.06.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon17.06.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture
Mon24.06.201913:00 - 15:00Seminarraum FAV EG B (Seminarraum von Neumann) Lecture

Examination modalities

Homeworks including programming exercises, student presentations and exam

Course registration

Begin End Deregistration end
25.02.2019 09:00 20.04.2019 23:59 20.04.2019 23:59

Curricula

Literature

No lecture notes are available.

Preceding courses

Accompanying courses

Language

English