Offene Themen für Bachelor- und Master-Arbeiten

Die folgende Liste enthält offene Themen für Bachelor- und Master-Arbeiten sowie für Pratika. Bitte beachten Sie, dass diese Liste nicht alle Themen enthält. Die wissenschaftlichen Mitarbeiter des Lehrstuhls bieten oft auf Nachfrage zusätzliche Themen in ihrem Interessengebiet an. Kontaktieren Sie sie gerne auf ihrer persönlichen Website.

Bei generellen Fragen wenden Sie sich bitte an Stefan Geißler.

Sie können sich eine Beschreibung des Themas anschauen, indem Sie den Abstract Link unter dem jeweiligen Eintrag anklicken. Dort sind auch die Kontaktinformationen des jeweiligen Betreuers angegeben.

Verfügbare Bachelorarbeiten

Supervisor: Metzger, F.: Profiling the E2E Delays of Streamed Video Games with the Camra Method, (2020).

[ Abstract ]

Determining the E2E lag of actions in video games is not trivial since there is no built-in way to grasp the full lag, including that contributed by the input and output. A standardized method is to record both input and output with a high framerate camera and count the frames from a visible input event to the result on screen. Your job is to perform these measurements for different actions in a series of games, and examine the overhead game streaming generates for them. Note: It might currently not be possible to perform these experiments, as they rely on a physical testbench.
Supervisor: Grigorjew, A.: Configuring Stream Aggregates with Timed Gates for Predictable Latency in Dynamic Networks, (2020).

[ Abstract ]

Time Synchronization and Timed Gates provide a popular mechanism for extremely low deterministic latency in Time-Sensitive Networking. Achieving the lowest latencies possible requires complex per-stream configuration and network-wide knowledge. This type of preparation is not possible in dynamic networks with varying traffic requirements and changing traffic patterns. This work is focused on the preparation of aggregate schedules that prepare time slots for a specific amount of traffic beforehand, which can be dynamically used by streams during the operation of the network. The challenges include the modeling of dynamic network requirements and, based on that, an optimal configuration of the number and length of transmission windows for each priority of this aggregate scheduling model.
Supervisor: Grigorjew, A.: Configuring Stream Aggregates with Asynchronous Traffic Shaping for Lower Latency, (2020).

[ Abstract ]

In Time-Sensitive Networking, Asynchronous Traffic Shaping (ATS) provides a per-stream shaping mechanism that lowers the worst case per-hop latency impact of interfering traffic. However, due to the per-stream reshaping of traffic at every hop, serialization benefits on high-bandwidth links cannot be utilized. Aggregating multiple streams into a single shaper state reduces their bursty impact and can possibly provide better latency guarantees. This thesis is designed around the idea of aggregate configuration, i.e., when do the benefits justify the extra configuration, and how does aggregate shaping influence the subsequent hops on the streams' paths.
Supervisor: Geissler, S.: Classification of IoT Signaling Incidents, (2020).

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Supervisor: Geissler, S.: Simulating IoT Interpolation Mechanisms to Improve Application Layer Information Quality, (2020).

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Supervisor: Loh, F.: Analyzing the Streaming Behavior of the Amazon Echo Show, (2020).
Supervisor: Schwind, A.: Crowdsourced Network Measurements: Evaluation and Applicability for 5G, (2020).

[ Abstract ]

Contact: anika.schwind@informatik.uni-wuerzburg.de
Supervisor: Seufert, M.: Evaluation of the Impact of Cross-Traffic on TCP and QUIC Video Streaming, (2020).

[ Abstract ]

Contact/Kontakt: michael.seufert@uni-wuerzburg.de Title: Evaluation of the Impact of Cross-Traffic on TCP and QUIC Video Streaming Abstract: The goal of this work is to prepare, conduct, and evaluate a measurements study, which investigates the impact of cross-traffic on TCP and QUIC video streaming. For that, an existing measurement framework can be reused. Moreover, impact factors with respect to the configuration of the transport protocols shall be identified and investigated in detail during this work. Titel: Auswertung des Einflusses von Störverkehr auf TCP- und QUIC-basiertes Videostreaming Inhalt: Das Ziel dieser Arbeit ist es eine Messstudie vorzubereiten, durchzuführen und auszuwerten bei der der Einfluss von Störverkehr auf TCP- und QUIC-basiertes Videostreaming untersucht wird. Dazu kann auf ein existierendes Messframework aufgesetzt werden. Im Verlauf der Arbeit sollen außerdem Einflussfaktoren bei der Konfiguration der Transportprotokolle identifiziert werden und genauer untersucht werden.
Gray, N.: Evaluation of the Impact of Network Topologies and Applications on Synchronization Strategies of Distributed SDN Controllers, (2020).

[ Abstract ]

Software-defined Networking (SDN) separates the data from the control plane and outsources the latter to a logically centralized instance called the controller. This enables a common view of the network topology and provides a central entity for network configurations. The controller is often distributed to impose no single point of failure and to balance the load efficiently among the physical controller instances. To maintain a consistent view of the network, synchronization between the individual controller instances is required. Controller implementations can be categorized by their utilized synchronization strategy and largely fall in one of two categories, namely horizontal or hierarchical. Goal of this thesis is to evaluate the impact of the network topology and running controller applications on the performance of the controller when using different synchronization mechanisms. As access to large SDN test beds is limited the investigations will be done by simulations within the OMNeT++ framework.

Verfügbare Masterarbeiten

Supervisor: Metzger, F.: Measuring the Effectiveness of Latency Mitigation Methods with a Prototype Video Game, (2020).

[ Abstract ]

Video games with a competitive multiplayer modes must deal with the troubles of high and varying end-to-end lag. They can employ varying methods to manage, mitigate or conceal this lag and equalize it between different clients. But the closed source nature of video games makes examining the effectiveness of these mechanisms hard. Your job is to implement a simple video game prototype from scratch that uses an authoritative client-server multiplayer approach and implements such lag mitigation mechanisms. With this prototype we want to get a better understanding of the effectiveness of these lag concealment measures.
Supervisor: Wamser, F.: Performance evaluation of distributed ledger technologies in networking, (2020).

[ Abstract ]

Das Ziel der Masterarbeit ist der Entwurf einer Methodik für die Ressourcenvergabe mittels Distributed Ledger-Verfahren (DLV) unter Einhaltung von Gütemetriken wie QoE und QoS. Die Grundlage hierfür sind flexible Verfahren für die Virtualisierung von Netz- und Rechenressourcen in Kombination mit skalierbaren verteilten Ledger-Verfahren zum System-Management und zur Abrechnung der zur Verfügung gestellten Ressourcen. Eine große Herausforderung für die angestrebte Ressourcenvergabe ist die hierarchiefreie Verteilung der Rechen- und Netzressourcen über mehrere Anbieter und Verwaltungsbereiche hinweg.
Supervisor: Schwind, A.: QoE Estimation of Music Streaming in the Network, (2020).

[ Abstract ]

Streaming made a lasting effect on the way our society consumes media in the last decade. While due to streaming the way we listen to music and podcasts has changed drastically, there are very few studies about its Quality of Experience (QoE) and how to predict the QoE under different network conditions. From subjective studies, we know that, for example, undesirable stops of the stream (stalling events) have a significant impact on QoE. This work focus on the estimation of the occurrence of such impact factors and thus, the QoE of the stream. The prediction is based on music streaming network traffic, which is typically encrypted. To collect data, a measurement framework will be set up and crowdsourcing studies will be conducted. Different monitoring methods will be applied (such as model-based or machine-learning-based monitoring) and their performance for estimating the QoE of music streaming will be evaluated. Contact: anika.schwind@informatik.uni-wuerzburg.de
Supervisor: Wehner, N.: Deep Learning for QoE Estimation, (2020).

[ Abstract ]

Contact/Kontakt: nikolas.wehner@uni-wuerzburg.de Auch als Praktikum verfügbar.
Supervisor: Geissler, S.: Simulation of a 5G Network Infrastructure, (2020).

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Supervisor: Loh, F.: A Simulative Approach to Study the Coverage of LoRaWAN in Würzburg, (2020).
Supervisor: Wehner, N.: Fingerprinting Websites in Encrypted Network Traffic, (2020).

[ Abstract ]

Contact/Kontakt: nikolas.wehner@informatik.uni-wuerzburg.de Auch als Praktikum verfügbar. Due to the encryption of network traffic and the introduction of DNS over HTTPS, the task of identifying websites based on the corresponding network traffic got difficult. Nonetheless, ISPs want to know which kind of traffic passes their networks in order to optimize the QoE of their customers. The goal of this work is to create a model which is able to reliably predict the called websites during a session. Therefore, reasonable features have to be extracted from the data and afterward they have to be ingested into selected Machine Learning algorithms.
Supervisor: Seufert, M.: Transfer Learning Approaches for QoE Monitoring of Encrypted Video Streaming Traffic, (2020).

[ Abstract ]

Contact/Kontakt: michael.seufert@uni-wuerzburg.de Title: Transfer Learning Approaches for QoE Monitoring of Encrypted Video Streaming Traffic Abstract: This work is focused on Quality of Experience (QoE) monitoring of encrypted video streaming traffic. Here, machine learning based methods are used to estimate QoE metrics based on features, which are extracted from the encrypted traffic. While these machine learning models achieve very good performance for a specific training data set, they typically show a worse performance when applied to different data sets. Thus, in this thesis, transfer learning approaches shall be tested and/or developed, which allow the existing models to generalize also over heterogeneous data sets. The performance of the transfer learning approaches shall be evaluated and a methodology for generalizing machine learning based QoE monitoring models shall be developed. Titel: Transferlernverfahren bei der QoE Messung auf verschlüsseltem Videostreamingverkehr Inhalt: Diese Arbeit beschäftigt sich mit der QoE Messung auf verschlüsseltem Videostreamingverkehr. Hierbei werden Methoden des maschinellen Lernens (ML) eingesetzt um QoE-Metriken zu schätzen basierend auf Features, die aus dem verschlüsselten Verkehr extrahiert werden. Während diese ML-Modelle sehr gute Leistung für spezifische Datensätze zeigen, haben sie typischerweise eine schlechtere Leistung wenn sie auf andere Datensätze angewandt werden. Deshalb sollen in dieser Arbeit Transferlernverfahren getestet und/oder entwickelt werden, die es erlauben, dass die existierenden Modelle auch für heterogene Datensätze verallgemeinert werden können. Die Leistung der Transferlernansätze soll bewertet werden und eine Methodik für die Generalisierung von ML-Modellen für QoE Messungen soll entwickelt werden.
Supervisor: Seufert, M.: Algorithms Towards Proactive QoE-aware Traffic Management, (2020).

[ Abstract ]

Contact/Kontakt: michael.seufert@uni-wuerzburg.de Title: Algorithms Towards Proactive QoE-aware Traffic Management Abstract: QoE-aware traffic management aims at improving the packet transmission and handling in the network in order to maximize the Quality of Experience (QoE) of Internet services. While most of today's approaches follow a reactive design, i.e., they change the traffic management only after a QoE degradation are detected or imminent, the focus of this work is to advance towards a more proactive design. This means algorithms shall be developed to improve the traffic management, such that it can be adjusted to changing network and service characteristics before QoE degradations can be noticed by the end users. In the thesis, also the performance of the algorithms shall be evaluated. Titel: Algorithmen für proaktives QoE-bewusstes Verkehrsmanagement Inhalt: QoE-bewusstes Verkehrsmanagement zielt darauf die Übertragung und den Umgang mit Paketen im Netzwerk zu verbessern, um damit die subjektive Dienstgüte (QoE) von Internetdiensten zu verbessern. Während die meisten der heutigen Ansätze eher ein reaktives Design haben, d.h., sie ändern das Verkehrsmanagement erst wenn eine Verschlechterung der QoE wahrgenommen wurde oder unmittelbar bevorsteht, liegt der Fokus dieser Arbeit darauf eine proaktiveres Design voranzubringen. Das bedeutet, dass Algorithmen entworfen werden sollen, um das Verkehrsmanagement zu verbessern, so dass es auf sich ändernde Netzwerk- und Dienstcharakteristika adaptiert werden kann bevor Verschlechterungen der QoE vom Endnutzer wahrgenommen werden können. In der Arbeit soll auch die Leistung der Algorithmen bewertet werden.
Supervisor: Seufert, M.: Estimating QoE of Web Browsing in the Network, (2020).

[ Abstract ]

Contact/Kontakt: michael.seufert@uni-wuerzburg.de Title: Estimating QoE of Web Browsing in the Network Abstract: This work is focused on Quality of Experience (QoE) of web browsing, i.e., the subjectively perceived goodness of the web browsing performance. First, known impact factors and metrics of web browsing (such as page load time, above the fold time, SpeedIndex) have to be tested and additional impact factors have to be identified. Afterwards, these impact factors have to be estimated from web browsing traffic, which is typically encrpyted. A measurement framework will be set up and crowdsourcing studies will be conducted to generate ground truth data. Different monitoring methods will be applied (such as model-based or machine-learning-based monitoring) and their performance for estimating the QoE of web browsing will be evaluated. Titel: Abschätzen der subjektiven Dienstgüte von Webbrowsing im Netzwerk Inhalt: Diese Arbeit beschäftigt sich mit der QoE von Webbrowsing, d.h., der subjektiven Güte des Webbrosing-Dienstes. Zuerst müssen bekannte Einflussfaktoren und Metriken (z.B. Seitenladezeit, "Über dem Knick"-Zeit, SpeedIndex) getestet werden und zusätzliche Einflussfaktoren identifiziert werden. Danach müssen diese Einflussfaktoren aus dem (typischerweise verschlüsselten) Webbrowsing-Netzwerkverkehr abgeschätzt werden. Ein Messframework wird aufgesetzt und Crowdsourcing-Studien werden durchgeführt um eine Datengrundlage zu erstellen. Verschiedene Monitoringansätze werden angewendet (z.B. modell- oder Machine-Learning-basiertes Monitoring) und ihre Leistungsfähigkeit beim Abschätzen der subjektiven Dienstgüte von Webbrowsing wird ausgewertet.

Verfügbare Praktika

Supervisor: Metzger, F.: Examining the Netcode of Old, Open-sourced Video Games, (2020).

[ Abstract ]

Video games have a long history of often competitive multiplayer modes, supported by various network implementations in their engines. The source code of many of these games has been open sourced over the years, opening their netcode up for examination. Your job is to extract the netcode from some of these games and compare them to each other. We want to find out, how the employed mechanisms have changed over time and how well they would fare in today's environment.
Supervisor: Metzger, F.: Designing a Realistic Virtual AQM Testbench, (2020).

[ Abstract ]

Many new queue management techniques and supporting technologies are currently being developed, standardized and rolled out. CoDel, Cake, PIE, DualPI just to name a few. Your job is to develop a portable virtual environment that allows for realistic tests and comparisons of these methods with automated test suits.
Supervisor: Wehner, N.: Implementation of a Low Latency QoE Fair HAS Logic, (2020).

[ Abstract ]

Contact/Kontakt: nikolas.wehner@uni-wuerzburg.de Auch als Masterarbeit verfügbar.
Supervisor: Loh, F.: Use Case Study of the Transmission Behavior of an Application Using LoRaWAN, (2020).
Supervisor: Schwind, A.: Investigating the QoE of Mobile Instant Messaging, (2020).

[ Abstract ]

WhatsApp is one of the most popular mobile instant messaging (MIM) applications. Due to MIM applications, the way we communicate has changed drastically. Nevertheless, there are very few studies about its Quality of Experience (QoE) and possible influence factors. Thus, the goal of this work is to evaluate the QoE MIM apps. Therefore, a web MIM application will be designed to simulate different possible influence factors on the QoE (e.g., image load times). Afterwards, a subjective user study will be conducted and QoE ratings on the simulated degradation will be collected and evaluated. Contact: anika.schwind@informatik.uni-wuerzburg.de
Supervisor: Seufert, M.: Characterization of Browsing Sessions, (2020).

[ Abstract ]

Contact/Kontakt: michael.seufert@uni-wuerzburg.de Title: Characterization of Browsing Sessions Abstract: The goal of this work is to characterize browsing sessions, which consist of visits to multiple web pages. In particular, the navigation timing between page visists shall be modelled. Titel: Charakterisierung von Browsingsessions Inhalt: Das Ziel dieser Arbeit ist die Charakterisierung von Browsingsessions, die üblicherweise aus Besuchen von mehreren Seiten bestehen. Insbesondere sollen dabei zeitliche Aspekte der Navigation modelliert werden.
Supervisor: Seufert, M.: Identifying User Behavior from Encrypted Video Streaming Traffic, (2020).

[ Abstract ]

Contact/Kontakt: michael.seufert@uni-wuerzburg.de Title: Identifying User Behavior from Encrypted Video Streaming Traffic Abstract: In this work, existing PC- and app-based measurement frameworks have to be modified to conduct video streaming measurements with emulated user interactions. Application and network layer streaming information shall be extracted and analyzed to identify the emulated user interactions from the encrypted streaming traffic. Titel: Indentifizierung von Nutzerverhalten aus verschlüsseltem Videostreaming-Netzwerkverkehr Inhalt: In dieser Arbeit sollen existierende PC- und App-basierte Messframeworks modifiziert werden, um Messungen von Videostreaming durchzuführen und Nutzerinteraktionen zu emulieren. Streaminginformationen sollen auf Applikations- und Netzwerkschicht extrahiert werden, um die emulierten Nutzerinteraktionen aus dem verschlüsselten Videostreaming-Netzwerkverkehr zu identifizieren.
Supervisor: Borchert, K.: Analysis and Correlation of objective and subjective Performance Data of an Enterprise Application, (2020).

[ Abstract ]

Contact: kathrin.borchert@informatik.uni-wuerzburg.de

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