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Update your Network: Loop Free! |
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Correct routing is one of the fundamental properties a network should provide, after all, packets must be able to reach their destination. However, sometimes routes have to change due to maintenance, failures, congestion etc. Even though the old and the new route provide reachability, the inherent asynchrony in networks could mean that temporarily networks get lost in a loop. For an example, see the above figure, where the task is to update from routing Tree 1 to Tree 2. If node v updates too slowly, packets will enter a loop, and subsequently get dropped as the buffers overflow. Even though modern programmable networks offer great flexibility how to handle this problem, there are still many open questions. In this thesis, you will be able to investigate this problem from both a practical and a theoretical perspective, according to your background and strengths. For example, you could implement your algorithmic ideas and benchmark them - how and when can current techniques be improved? First steps
What we offer
Expected knowledge
Keywords: Algorithm engineering, graph algorithms, routing, consistency If you are interested, contact us and we can discuss possible directions for your thesis/project. To get a feeling for some past research on these topics (non-exhaustive), please feel free to look at the following:
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This topic is available at all levels. |
Checking for Upgrades in a Continuous Event-Emitting Deployment |
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As part of Thoth Station’s knowledge aggregation, there are several packages inside a continuous deployment infrastructure. The goal of this project is to enable automatic alerts and, depending on the level of the project, enable automatic upgrades within the system. First steps:
This project allows helps you to:
Prerequisites:
Nice to have:
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For more information on Project Thoth and/or if you would like to take this project, please contact sanja.bonic@univie.ac.at. |
Algorithmically Find Correlations in a Data Set of Runtime Environment Inspections |
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As part of Thoth Station’s overall infrastructure knowledge gathering, the aim of this project is to algorithmically find correlations (or prove their nonexistence) in a provided data set of inspections. These inspections include, but are not limited to:
The inspections are run as pods via OpenShift. In order to find out more about Thoth and how this project contributes to building a knowledge graph and a recommendation system for application stacks based on the collected knowledge, read more at https://developers.redhat.com/blog/2019/10/28/microbenchmarks-for-ai-applications-using-red-hat-openshift-on-psi-in-project-thoth/. This project allows helps you to:
Prerequisites:
Nice to have:
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For more information on Project Thoth and/or if you would like to take this project, please contact sanja.bonic@univie.ac.at. |
Draw Simplified Icon Representations of Nouns Given via Various Inputs |
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As part of a larger ML project that will be open sourced, this part of the project is about drawing several icon representations of nouns within one image. You will take as input a list of nouns and let the computer represent those nouns via icons/sketches in an image file. First steps:
This project helps you to:
Prerequisites:
Nice to have:
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This topic is available at all levels. For more information, please contactstefan_schmid@univie.ac.at or sanja.bonic@univie.ac.at. |
Determine Composition Value in Images |
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As part of a larger ML project that will be open sourced, this part of the project is about determining composition value in images. You will find images with a license that allows usage in research projects and find a way to determine their composition value. You will then feed this information to an ML algorithm that will be used in the subsequent parts of this overall project. First steps:
This project helps you to:
Prerequisites:
Nice to have:
Reading starters:
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This topic is available at all levels. For more information, please contactstefan_schmid@univie.ac.at or sanja.bonic@univie.ac.at. |
Determine Position and Evaluate Area Percentage in Images |
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As part of a larger ML project that will be open sourced, this part of the project is about recognizing the position of objects in images and defining the area percentage these objects take within the image. You will then feed this information to an ML algorithm that will be used in the subsequent parts of this overall project. First steps:
Research questions:
This project helps you to:
Prerequisites:
Nice to have:
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This topic is available at all levels. For more information, please contactstefan_schmid@univie.ac.at or sanja.bonic@univie.ac.at. |
Should you have your own idea for a potential thesis which you think might fit the research interests of our group, do not hesitate to contact us directly. It can be related to the topics above, but also something completely different, as long as it roughly fits into our area. |
This topic is available at all levels. For more information, please contact Prof Stefan Schmid atstefan_schmid@univie.ac.at |
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