Curriculum on Self-Organizing Networked Systems
Contents
Curriculum
Core Courses
The following courses are mandatory:
Introduction to Self-Organizing Networked Systems
- Part I: What is a self-organizing system? Methodology and theory. Links to following courses.
- Part II: Case studies. A ring lecture with speakers from different universities and different fields.
Dynamic Systems
Lecture and Lab
Content: similar to "Nonlinear Dynamics and Chaos" by Steven H. Strogatz
Textbooks:
- Nonlinear Dynamics and Chaos by Steven H. Strogatz
Network Theory
Lecture and Exercises
Content: Networks from the real world. Network topology: Graph theory basics, random graphs, phenomena small wold and scale-freeness. Network functions/processes/algorithms: E.g. search, percolation.
Information Theory and Coding
Lecture and Exercises
Advanced Stochastics
Lecture and Exercises
Content: Selected topics from the following fields: Stochastic Processes. Statistical Physics.
Intelligent Systems (?)
Game theory: Cooperation (Prisoneer's Dilemma), economic behavior
Neural networks: introduction to biological neural networks, Artificial Neural Networks, topologies (Multilayer, recurrent, fully meshed), Self-Organizing Feature Maps, spiking neural networks, emergent patterns in ANN
Machine learning: Genetic algorithms, simulated anneahling, Sintflut algorithm, rule-based learning, bayesian networks
Modeling and Simulation (?)
Algorithms and Data Structures
Lecture and Lab.
Content: Sorting and searching, tree-based structures, graph algorithms (over), recursive algorithms, complexity classes and computational effort.
Textbooks:
- The Algorithm Design Manual by Steven S. Skiena
- Introduction to Algorithms by Charles E. Leiserson, Ronald L. Rivest, Clifford Stein
Control Theory
control loop, stability, distributed control, event-based control, MIMO control systems
Catch-up Courses
Depending on the background of the student, she or he attends a subset of the following courses:
Specialization 1: Communication Networks
Mobile and Wireless Systems
Contents: Introduction and overview. Radio propagation. Coding, modulation, and duplexing. Multiple access and cellular concept. Medium access control (MAC) protocols. Wireless LAN 802.11. Network architecture and mobility protocols. Security in mobile networks. Multihop networks. Economic, health, and social aspects.
Sensor Networks
Peer-to-Peer Networks
Protocol Engineering
Group Work
Group 1: Bauschert, Bettstetter, Pletzer, Quaritsch, Yanmaz
Group 2: Anton, Manfred, Felix, Johannes,Alain
All courses should specifically deal with applications towards SOS.
Curriculum table
Subject | Type | g1 grad | g2 und.grad | g2 grad | g2 grad spec. | g3 | g4 | ||
---|---|---|---|---|---|---|---|---|---|
Dynamical Systems | Lecture | X | X | ||||||
Information Theory | Lecture | X | |||||||
Algorithms 1 | Lecture & Lab | X | |||||||
Algorithms 2 | Lecture & Lab | X | |||||||
Distributed Algorithms | X | ||||||||
Game Theory | X | ||||||||
Numerical Simulations | Lecture & Labs | X | |||||||
Modeling and Simulation | Lecture & Labs | X | |||||||
Topics course SO in nature/society | Lecture | X | |||||||
Network 1 | X | X | |||||||
Network 2 | X | X | |||||||
Statistical physics 1 & 2 | X | ||||||||
Embedded Systems | X | ||||||||
Sensors and Robotics | X | ||||||||
Calculus 1 & 2 | Lecture | X | |||||||
Statistics | Lecture | X | |||||||
Diff. Equations | Lecture | X | |||||||
Linear Algebra | Lecture | X | |||||||
Programming | Lecture | X | |||||||
Natural sciences | Lecture | X | |||||||
Mobile&Wireless Systems | X | ||||||||
Sensor Networks | X | ||||||||
Peer-to-Peer Networks | X | ||||||||
Information Theory and Coding | X | ||||||||
Protocol Engineering | X | ||||||||
Physics | bacc | ||||||||
Applied Mathematics | bacc | ||||||||
Biology | bacc |
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