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
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 (?)
Content: Game theory, neural networks, machine learning
Modeling and Simulation (?)
Algorithms & 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
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 | |||||||
Information Theory | Lecture | X | |||||||
Algorithms 1 | Lecture & Lab | X | |||||||
Algorithms 2 | Lecture & Lab | X | |||||||
Numerical Simulations | Lecture & Labs | X | |||||||
Topics course SO in nature/society | Lecture | X | |||||||
Network 1 | X | ||||||||
Network 2 | 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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