Main document
Networked Embedded Systems [NES]
L.079.05512, Winter 2014/2015
Content
The objective of this course is gain insights into the operation and programming of embedded systems. A strong focus is on wireless sensor networks. We study the fundamentals of such sensor networks. In the scope of the exercises, we discuss selected topics in more detail.
- Design and architecture of embedded systems
Architecture of embedded systems, programming paradigms - Sensor networks
Principles and applications - Wireless communications
Concepts of modulation and encoding on the physical layer - Wireless access
Typical medium access protocols for low-power sensor nodes - Routing
Ad hoc routing and data centric communication - Clustering
Clustering algorithms, guaranteed connectivity - Localization
Ranging techniques, localization algorithms
Learning Outcome
The learning objective is to unserstand the fundamental concepts of networded embedded systems. Students understand these concepts and are able to apply this knowledge.
General Information / Methods
This bachelor course will be held in English and all the course material is available in English.
- 4 ECTS (Lecture: 2 SWS, Exercises: 1 SWS)
Instructors
- Lecture: Falko Dressler
- Exercises: Christoph Sommer, Bastian Bloessl
Schedule
-
Lecture
Thursday, 4:15pm - 5:45pm, O2 -
Exercises
Friday, 10:15am - 11:00am, F1.520 (PC pool 1st floor)
Friday, 11:15am - 12:00pm, F1.520 (PC pool 1st floor)
Exams
Oral examination (by appointment)
Evaluation
Many thanks for the critical and helpful evaluation!
Literature
Falko Dressler, Self-Organization in Sensor and Actor Networks, Chichester, United Kingdom, John Wiley & Sons (Wiley), 2007. [DOI, BibTeX, Details...]
Holger Karl and Andreas Willig, Protocols and Architectures for Wireless Sensor Networks, Chichester, United Kingdom, John Wiley & Sons (Wiley), 2005. [DOI, BibTeX, Details...]
Ian F. Akyildiz and Mehmet C. Vuran, Wireless Sensor Networks, Chichester, United Kingdom, John Wiley & Sons (Wiley), 2010. [DOI, BibTeX, Details...]
Extras
Featured Paper
- Explainability of Neural Networks for Symbol Detection in Molecular
Communication Channels
Recent research in molecular communication (MC) suggests machine learning (ML) models for symbol detection, avoiding the unfeasibility of end-to-end channel models. Ho...
News
- November 15, 2023
Keynote at IEEE LATINCOM 2023
Falko Dressler gave a keynote titled 6G Virtualized Edge ... - November 03, 2023
Talk at KAIST Seminar on Mobile & Wireless in EE
Falko Dressler gave a seminar talk titled Virtualized Edg... - October 12, 2023
Paper presentation at IEEE VTC 2023-Fall
Atefeh Rezaei presented our paper titled Resource Allocat... - October 03, 2023
Paper presentation at European Wireless 2023
Agon Memedi presented our paper titled One-Class Support ... - October 02, 2023
Poster presentation at ACM MobiCom 2023
Jonas Kuß presented our paper titled A Measurement Syste...