TU Wien:Energy-Efficient Distributed Systems VU (Brandic)

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Lecturers [tiss.person:51423 Brandic, Ivona], [tiss.person:298062 Lujic, Ivan]
ECTS 3 / 4,5
Department Institut für Information Systems Engineering
When summer semester
Language English
Links tiss:194049, Homepage
Master Data Science Pflichtmodul BDHPC/CO - Big Data and High Performance Computing - Core



8 lectures held by three lecturers:

  • Introduction to energy-efficient distributed systems
  • Taxonomy on energy-efficient systems
  • Autonomic cloud management
  • Current forms of distributed systems
  • Fuzzy hand-off control
  • Code offloading
  • Geo-temporal conditions
  • Controller design for clouds

+ another lecture where the assignment is introduced



  • Lecture part: oral exam at the end of the semester (see below)
  • Exercise part: Assignment (semester project) to be done in groups of 3

Benötigte/Empfehlenswerte Vorkenntnisse[edit]


  • Programming skills
  • At least basic knowledge about Statistical Learning/Machine Learning



The majority of slide decks (and thus also the covered material) are a compilation of research papers.



Semester project to be done in groups of 3: Energy-aware scheduling of virtual machines using the GWA-T-12 Bitbrains fastStorage dataset (http://gwa.ewi.tudelft.nl/datasets/gwa-t-12-bitbrains). Students were free to choose their preferred programming language and libraries/frameworks.

Overall tasks:

  • Find a suitable technique to predict the CPU utilization of virtual machines (e.g., regression models, time series models, LSTM, ...)
  • Implement 2 given algorithms + one own algorithm for energy-aware scheduling of virtual machines
  • Write a program to simulate the scheduling of virtual machines on physical machines and compare the energy consumption of the scheduling algorithms
  • Summarize your findings in a report.

The progress of the project has to be presented during the semester (2 intermediate presentations) + a final presentation at the end of the semester.

Prüfung, Benotung[edit]


50% oral exam, 50% exercise part

Oral exam is done in slots, 4 students in each slot. 3 questions per student:

  1. Question about the exercise part
  2. Question about the lecture part
  3. Question on a research paper (the research paper is assigned on a per-slot basis ~1 week in advance)

Selection of assigned research papers:

Dauer der Zeugnisausstellung[edit]

Semester Letzte Leistung Zeugnis
2022S 01.07.2022 11.07.2022


Within 3 ECTS (given sufficient programming knowledge, background in Statistical Learning/Machine Learning and a decent group)


noch offen


noch offen

Verbesserungsvorschläge / Kritik[edit]


  • Depending on the presentation slot you are in, you might not get any feedback on your exercise progress
  • There is no feedback on the oral exam - at all (you just get the certificate)
  • IMHO, the lecture lacks a common theme (besides the fact that everything is somehow related to distributed systems or energy efficiency).


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