| Module: | Network Simulation |
| Module number: | 41.5050 |
| Language: | english |
| Study programme: | Dualer Master 2021 - Katalog AS: Anwendungs- und systemorientierte Module
Master 2021 - Katalog AS: Anwendungs- und systemorientierte Module
Dualer Master 2013 - Katalog AS: Anwendungs- und systemorientierte Module
Master 2013 - Katalog AS: Anwendungs- und systemorientierte Module
MN Data Science 2016 - Katalog M-I_I: Allgemeine Wahlpflicht Informatik |
| Type of course: | VP = Lecture with integrated Practical |
| Weekly hours: | 4 |
| Credit Points: | 6 |
| Registering for exam | explicitly and independent of booking |
| Frequency of offering: | each summer semester (lastly in SS 2022) |
| Required knowledge: | Solid programming skills in C++ and Basics in Computer Networks |
| Learning objectives: | Network Simulations are used to study the behavior of computer networks in software. In this practical course, students will program their own network simulations in C++.
Supported by a state-of-the-art simulation engine, students
- will learn how to model, study and benchmark essential parts of communication networks (e.g., wireless and wired links, Internet routers, cellular base stations, Web servers).
- will be trained to differentiate meaningful results from randomness, to avoid common pitfalls in simulation design and result interpretation, as well as to plan for large simulations at scale.
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| Content: | - Essential statistics: Random variables, probability distributions, Goodness of Fit tests
- Simulation concepts and background: Monte-Carlo, Discrete-Event, random number generation, the OMNeT++ simulation framework
- Models and data structures for Network Simulation: Selecting distributions, arrival processes, network traffic models, queueing systems, heaps & Co.
- Interpreting output data: estimating means, computing confidence intervals, comparing systems, handling correlation, (in)validating models
- Planning simulations: Experimental design, 2k factorial designs, metamodels
- Common pitfalls: Parallel random number generation, initial transient, multivariate processes, dependent factors
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| Literature: | - A. Law, Simulation Modeling and Analysis, 5th edition, 2006.
- Jack L. Burbank, William Kasch, Jon Ward, An Introduction to Network Modeling and Simulation for the Practicing Engineer, 2011.
- A. Varga, "OMNeT++ User Guide", available at: https://omnetpp.org, 2016
- Further references will be provided during the lecture
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| Lecture style / Teaching aids: | The course will take place in a computer lab: Computers, software, and source code examples will be provided. Students can use their own Laptops as well. |
| Responsibility: | Stefan Valentin |
| Released: | SS 2019 |
| Offered in SS 22: | Valentin |
| Professional competencies: | - formal, algorithmic, mathematical competencies: medium
- analytical, design and implementation competencies: high
- technological competencies: medium (C++, computer networks)
- capability for scientific work: medium
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| Interdisciplinary competencies: | - project related competencies: depending on subject
- interdisciplinary expertise: Basics in processing numerical data and its visualization
- social and self-competencies: ability to work in a team
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