| Vorlesung Theory of Distributed Systems | Lecture Theory of Distributed Systems | 0 | 3 |
| Übung Theory of Distributed Systems | Excercise Theory of Distributed Systems | 0 | 2 |
| Prüfung Theory of Distributed Systems | Exam Theory of Distributed Systems | 6 | 0 |
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### 3. Studien- und Prüfungsleistungen
*[Erläuterungen zu Abschnitt 3](../Anleitungen_Hilfen/3_Leistungen.md)*
**(!) Teilnahmevoraussetzungen (DE)**
Keine.
**(!) Teilnahmevoraussetzungen (EN)**
None.
**(!) Prüfungsbedingungen (DE)**
Klausur oder mündliche Prüfung (100 %). Voraussetzung für die Zulassung zur Prüfung ist das Bestehen von Hausaufgaben.
**(!) Prüfungsbedingungen (EN)**
Written exam or oral examination (100 %). Students must pass written homework to be admitted to the module examination.
### 4. Informationen für das Modulhandbuch
*[Erläuterungen zu Abschnitt 4](../Anleitungen_Hilfen/4_Infos_Modulhandbuch.md)*
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**(!) Empfohlene Voraussetzungen (DE)**
Basic knowledge about algorithms, discrete structures, and probability theory.
**(!) Empfohlene Voraussetzungen (EN)**
Basic knowledge about algorithms, discrete structures, and probability theory.
**(!) Lernziele (DE)**
**Knowledge:** After successful completion of the module students know
* how to describe foundational problems arising in distributed systems and explain algorithmic solutions for these problems.
**Skills:** After successful completion of the module, students will be able to
* apply general algorithmic design principles like randomized contention resolution and congestion avoidance and to use techniques like load balancing and randomization to solve problems arising in network contexts.
**Competencies:** Based on the knowledge and skills acquired in the module, students will be able to
* model distributed systems in a formal way and to develop algorithmic solutions enabling the efficient usage of computer networks and other distributed systems.
**(!) Lernziele (EN)**
**Knowledge:** After successful completion of the module students know
* how to describe foundational problems arising in distributed systems and explain algorithmic solutions for these problems.
**Skills:** After successful completion of the module, students will be able to
* apply general algorithmic design principles like randomized contention resolution and congestion avoidance and to use techniques like load balancing and randomization to solve problems arising in network contexts.
**Competencies:** Based on the knowledge and skills acquired in the module, students will be able to
* model distributed systems in a formal way and to develop algorithmic solutions enabling the efficient usage of computer networks and other distributed systems.
**(!) Inhalt (DE)**
* Algorithms in message-passing systems
* Leader election and consensus
* Routing in networks: centralized and distributed approaches
* Randomized methods for contention resolution and congestion avoidance
* Contagion and Distributed Network Dynamics
* Game theoretic models and solution concept
**(!) Inhalt (EN)**
* Algorithms in message-passing systems
* Leader election and consensus
* Routing in networks: centralized and distributed approaches
* Randomized methods for contention resolution and congestion avoidance
* Contagion and Distributed Network Dynamics
* Game theoretic models and solution concept
**(!) Literatur**
* Leighton. Introduction to Parallel Algorithms and Architectures: Arrays, Trees, Hypercubes
* Kurose, Ross: Computer Networking: A Top-Down Approach Featuring the Internet. Addison Wesley Longman, 1999.
