Komplexpraktikum "Networked Systems Modeling" 2022s [PR 2022s]
(0/0/4) ET-INF-D-900, INF-04-FG-SOI, INF-04-KP, INF-B-510, INF-B-520, INF-B-530, INF-B-540, INF-MA-PR, IST-05-KP, Summer 2022
- ⏰ Time and Date: by arrangement (first plenary meeting: Friday, 2. DS (09:20))
- 🟢 Start: 1st week of teaching period
- 👋 Location: room APB E006 or BigBlueButton https://bbb.tu-dresden.de/b/bur-yjd-ryc-yup, presentations preferred in-person (E006), other meetings preferred online (BBB)
- 📦 Format: 🏛 on-campus class and/or web meeting (see “Location”), 📁 slide/sheet download, 💬 chat
- 🧰 Prerequisites: see section “Prerequisites”
- 💬 Questions? Comments? Join the discussion in our Matrix Room #nsm-course-pr:tu-dresden.de (reachable from the TU Dresden Matrix server)
Contents
The goal of this lab is to get practical experience in modeling and simulation of networked systems. You will actively take part in research, working on a small semester-long task individually or in small groups. The tasks are taken from the context of cooperative mobile systems, but the developed skills in model generation, simulation design, statistics, and result presentation are helpful in a broad range of application domains.
Each participant (or small group of participants) will choose a single task from a pool of tasks (see OPAL) to work on during the semester. Solving this single task is enough to pass the course.
Prerequisites
This class may have substantial online components. To be able to join, you must be able to make use of
- your university e-mail mailbox, reading its messages daily
(e.g., by configuring it to forward to your private mailbox) - OPAL and associated services, reading its messages daily
(e.g., by configuring e-mail notifications) - web chat systems, particularly the TU Dresden Matrix server
- web video conferencing systems, particularly via BigBlueButton (Test Room)
- a virtual machine, e.g., using Oracle VM VirtualBox
Before enrolling, please try these out and contact us if you do not fulfill these requirements.
Beyond this, there are no formal prerequisites for joining. Still, certain background knowledge is not taught in this course, but assumed for the course.
- You should have a background (or the willingness to learn) computer networking with a focus on wireless as well as fundamental knowledge of applied statistics.
- Simulations will be designed, written (in C++), and run (on Linux systems). For this, both programming and computer skills are essential.
Background knowledge in either “Network Simulation” or “Cooperative Mobile Systems” is helpful for the labs. However, all tasks are designed so that it is also easily possible to solve them without taking the courses (albeit with a little more time to get familiar with the simulation software and car-to-x communication). Grading at the end of the course will take this into account. Please ask your instructors for details.
Learning Outcome
See “Contents”.
General Information / Methods
This course will be held in English (German, if universally preferred) and all the course material is available in English. The teaching platform for this course is OPAL.
For participation, the following mode is fixed:
- Plenary meetings will be conducted on-campus (if desired: as a web meeting). Our streaming platform is the TU Dresden BigBlueButton instance, with Zoom as a fall-back. Times and dates as well as links will be published here.
- One-to-one interactions are up to participants and involved researchers.
Questions? Comments? Join the discussion in our Matrix Room #nsm-course-pr:tu-dresden.de (reachable from the TU Dresden Matrix server) or add a post to our OPAL forum!
Grading
Grades will be based on deliverables.
If you want to get a grade, please pre-register the exam with us in the first two weeks of lecture. This is in addition to the regular exam registration you will need to do later in the semester. See the organizational slide deck for details.
Instructors
Preliminary information
Our first plenary meeting will be in the first week of the teaching period.
Further organizational details will likely reflect that of last semester’s course.