Intern
Lehrstuhl für Informatik III

Bachelorthesis

Previous Bachelor Theses

2024[ to top ]
  • 1.
    Urban, K.: Designing a Crowdsourcing Study for the Interaction of Web QoE and User Engagement, (2024).
2023[ to top ]
  • 1.
    Michler, J.: Correlating Machine Learning Confidence to Outlier Detection for Network Monitoring Tasks, (2023).
  • 1.
    Karl, L.: Design, Implementation, and Execution of a QoE Study for Short Video Services, (2023).
  • 1.
    Full, D.: Investigating Quality of Experience of Video Conferencing via Crowdsourcing, (2023).
  • 1.
    Steinbeck, A.: Network Measurement of Mobile Instant Messaging Traffic, (2023).
  • 1.
    Komander-Gaitan, P.: Measurement of Social Networks within Mobile Messaging Applications, (2023).
  • 1.
    Ostermann, M.: Improving Web QoE Estimation with Contrastive Learning, (2023).
  • 1.
    Werner, D.: Simulative Evaluation of (In-)Confident Machine Learning for User-based Active Learning, (2023).
2022[ to top ]
  • 1.
    Hufen, S.: OMNeT++ Simulation for Investigating the Impact of Edge Caching for Mobile Instant Messaging, (2022).
  • 1.
    Kilicarslan, S.: Simulative Performance Evaluation of Device-to-Device-based Mobile Messaging, (2022).
  • 1.
    Amir, M.: Relating Google’s Web Vitals and Web QoE in a Crowdsourcing Approach, (2022).
  • 1.
    Rduch, T.: Investigation of Fundamental Differences in the Perception of Web Browsing and Video Streaming Quality of Experience, (2022).
  • 1.
    Pham, T.T.: Quantifying the Influence of Consent Banners on Web QoE with Crowdsourcing, (2022).
  • 1.
    Frieling, M.: Evaluating the Interaction between Web and Video QoE with Crowdsourcing, (2022).
  • 1.
    Glauer, S.: Experimental Evaluation Tool for Exploring User-based Active Learning for ML-based Browser and URL Detection, (2022).
2021[ to top ]
  • 1.
    Schweifler, R.: Evaluating the Impact of Browsing Delays on the QoE of Music Streaming, (2021).
  • 1.
    Oesen, E.: Machine Learning Based Web QoE Monitoring for Encrypted Network Traffic, (2021).
  • 1.
    Engelbrecht, T.: Investigating the Relationship of Network Data Arrival and the Rendering Process in Chrome, (2021).
  • 1.
    Sichermann, M.: Evaluting the Mobile Internet Experience in Bavaria from End User Perspective, (2021).
  • 1.
    Schumann, L.K.: Investigation of Hardware and Software Timestamping in Different Network Interfaces, (2021).
  • 1.
    An, S.H.: Investigation of Timed Gates for Predictable Latency in Dynamic Networks, (2021).
  • 1.
    Knaub, A.: Investigation of Stream Aggregates for Asynchronous Traffic Shaping, (2021).
  • 1.
    Arslanian, A.: QoE Study for Compatible Video and Web Browsing QoE Models, (2021).
  • 1.
    Wieser, V.: Bandwidth Measurements in Mobile Scenarios using a Raspberry Pi, (2021).
  • 1.
    Khelloqi, S.: Evaluation of Data Augmentation for Machine Learning on Network Traffic, (2021).
  • 1.
    Bühler, M.: Modelling the Communication behavior in WhatsApp, (2021).
  • 1.
    Ebner, M.: Plausible Performance Prediction of Simulated SDN-enabled Networks via Machine Learning, (2021).
  • 1.
    Schmitt, P.: Exploratory Comparison of Contemporary Cloud Gaming Services, (2021).
  • 1.
    Theiner, M.: Profiling the E2E Delays of Streamed Video Games with the Camera Method, (2021).
  • 1.
    Funk, M.S.: Comparing Video QoE Models Using Subjective QoE Data Sets, (2021).
2020[ to top ]
  • 1.
    Mertinat, N.: Impact of Content Selection on Crowdsourced QoE Studies of HTTP Adaptive Streaming on Mobile Devices, (2020).
  • 1.
    Gray, N.: Evaluation of the Impact of Network Topologies and Applications on Synchronization Strategies of Distributed SDN Controllers, (2020).
  • 1.
    Dworschak, N.-D.: Evaluating Temporal Impairments in Music Streaming, (2020).
  • 1.
    Halloway, M.: Investigating the Influence of App Browsing Delays on the QoE of Music Streaming, (2020).
  • 1.
    Fehler, H.: Comparison of Web QoE Algorithms on Different Devices, (2020).
  • 1.
    Kargl, J.: Analysis of QoE Aspects of 3D Point Cloud Reduction, (2020).
  • 1.
    Hessenauer, L.: Classification of IoT Signaling Incidents, (2020).
  • 1.
    Carsai, C.: Performance Evaluation of Actor-based Softwarized Network Functions, (2020).
  • 1.
    Hofmann, J.: Deep Reinforcement Learning for Configuration of Time-Sensitive-Networking, (2020).
  • 1.
    Aliev, E.: Evaluation of the Impact of Web Cross-Traffic on TCP and QUIC Video Streaming, (2020).
2019[ to top ]
  • 1.
    Janiak, T.: Investigating the Influence of Listener Attentiveness on the QoE of Music Streaming, (2019).
  • 1.
    Kurak, T.: Subjektive Nutzerstudie zur Untersuchung des Einflusses von persönlicher Bekanntheit und Popularität eines Videos auf die QoE, (2019).
  • 1.
    Haberzettl, L.: QoS Assessments of Spotify’s Mobile Application for Audio Streaming, (2019).
  • 1.
    Ewald, M.: Observing Changes in Machine Learning Behavior from Input Latency in Games, (2019).
  • 1.
    Hildebrand, K.: Towards a Source Traffic Model for Instant Messaging using WhatsApp, (2019).
  • 1.
    Wolz, M.: Hit Detection with Asymmetric Latency in UE4 Authoritative Multiplayer Games, (2019).
  • 1.
    Leidinger, F.: Studing the Initial Delay of the YouTube Mobile App with TensorFlow, (2019).
  • 1.
    Simonovski, F.: Studying the Video Segmentation for different Streaming Platforms, (2019).
2018[ to top ]
  • 1.
    Bocerov, M.: Videokompressionsverfahren und ihre Eignung für Adaptives Videostreaming, (2018).
  • 1.
    Hefter, J.: Analyzing the Streaming Behaviour of a Popular Video-On-Demand Service, (2018).
  • 1.
    Vomhoff, V.: Traffic Measurement Study of the Amazon Echo Show, (2018).
  • 1.
    Wollek, A.: Validierung eines generischen HAS-Modells für unterschiedliche Heuristiken., (2018).
  • 1.
    Janiak, L.: Impact of the measurement design on application behavior of video streaming, (2018).
  • 1.
    Katzmareck, M.: Identifying Relationship Pattern within WhatsApp, (2018).
  • 1.
    Borst, V.: Experimental Evaluation of the Interface Design of Crowdsourcing Tasks, (2018).
  • 1.
    Poignée, F.: Influence of Tension on QoE in Video Streaming, (2018).
  • 1.
    Gölz, J.: Evaluation of the Movement Synchronization of Unreal Engine 4, (2018).
  • 1.
    Weber, K.: Machine Learning for Classification of Streaming Data, (2018).
2017[ to top ]
  • 1.
    Shweiki, R.: Determination of Traffic Patterns by a Remote Controllable Drone, (2017).
  • 1.
    Abd El Hai, S.: Measuring the Applicability of the Analytic Model for SDN Controller Traffic and Switch Table Occupancy, (2017).
  • 1.
    Sträßer, M.: SDN-based Elephant Detection, (2017).
  • 1.
    Bocerov, M.: Video Encoding Techniques and their Impact on the Trade-off between Bitrate and Video Quality, (2017).
  • 1.
    Popp, C.: Study on the Accuracy of Video Monitoring VNF in High Mobility Environments, (2017).
  • 1.
    Flaig, N.: Simulative Performance Comparison of Adaptation Logics for HTTP Adaptive Streaming, (2017).
  • 1.
    Smietanka, O.: Detecting People Flows with Distributed Loudness Sensors, (2017).
  • 1.
    Stulier, N.: Evaluation of Cranial Deformations Using Crowdsourcing, (2017).
  • 1.
    Bauer, A.: Impact of Game Mods on Game Sales and Player Behavior, (2017).
  • 1.
    Waigand, M.: Towards Traffic Management for Mobile Group-based Communication in WhatsApp, (2017).
  • 1.
    Waigand, P.: Predictive Modeling of Video Spreading in Online Social Networks, (2017).
  • 1.
    Rosenberger, A.: Evaluation of the Stability of BGP Routes Based on RTT Measurements, (2017).
  • 1.
    Tschammler, F.: Relationship between Context and QoE for Video Streaming, (2017).
  • 1.
    Tönsing, L.: Semi-automated Generation of Image Annotations using Crowdsourcing and Tools for automated Translation, (2017).
2016[ to top ]
  • 1.
    Romaguera, F.: Influence of Task Granularity on the Quality of Results in Crowdsourcing, (2016).
  • 1.
    Winkler, T.: Developement of a Web-based Library for Collecting Hard- and Software Context Information, (2016).
  • 1.
    Ott, S.: Browser-based Measurements of HTTP Live Streaming Performance, (2016).
  • 1.
    Landbeck, D.: Framework for Simulative Performance Evaluation of HTTP Adaptive Video Streaming, (2016).
  • 1.
    Ott, M.: Performance Evaluation of Caching Architectures using the Internet Proxy Squid, (2016).
  • 1.
    Berani, S.: Evaluation of an Adaptive Flow Monitoring Implementation for SDN-based Networks, (2016).
  • 1.
    Ernst, F.: Einfluss von Netzwerkparamtern auf Synchronisationsmechanismen in Videospielen, (2016).
  • 1.
    Sasu, B.: Investigation of Analytical Modeling Approaches for Edge Computing, (2016).
  • 1.
    Zeidler, B.: Comparison of Machine Learning Approaches for YouTube Video Adaptation Estimation on Encrypted Traffic, (2016).
  • 1.
    Zorn, F.: Methods for Improving the Qualitiy of Experience of Mobile Video Streams, (2016).
  • 1.
    Knapp, T.: Assessment of the ONOS SDN Controller in Case of Network Errors, (2016).
  • 1.
    Raffeck, S.: Benchmarking SDN Controller with OFCProbe, (2016).
2015[ to top ]
  • 1.
    Gensler, T.: Analysis of Friendliness in Software Development Communities, (2015).
  • 1.
    Schwind, A.: Classification and Modeling of Group-based Communication in WhatsApp, (2015).
  • 1.
    Wehner, N.: Automated Quality Evaluation of HTTP Adaptive Video Streaming with an Android App, (2015).
  • 1.
    Lesch, V.: Estimating Worker Attention on Microtasking Platforms, (2015).
  • 1.
    Züfle, M.: Testbed-based Comparison of Application-Aware Traffic Management Strategies, (2015).
  • 1.
    Konrad, C.: Automated Evaluation of Group-based Communication in WhatsApp, (2015).
  • 1.
    Lazarus, S.: Aging and Scaling of Online Social Networks Graphs, (2015).
  • 1.
    Herrnleben, S.: Towards an Emulation of a Multi-Table OpenFlow Switch through a Proxy Layer, (2015).
2014[ to top ]
  • 1.
    Loh, F.: Determination of Traffic Patterns of the Facebook Mobile App and the WhatsApp Messenger, (2014).
  • 1.
    Werthmann, A.: Implementation and Evaluation of Extended Resilience Metrics for the Pareto-Optimal Controller Placement in SDN-based Networks, (2014).
  • 1.
    Beutel, A.: Comparison of Active and Passive Measurements of the Application Behaviour in Enterprise Networks with Thin-Client Architecture, (2014).
  • 1.
    Stauch, S.: Modeling the Distribution of Home Routers in the Internet, (2014).
  • 1.
    Borsos, R.: Social Network Analysis of Software Development Mailing Lists, (2014).
  • 1.
    Bauer, A.: On Algorithms for Socially-Aware Prediction of Individual Content Requests, (2014).
  • 1.
    Griepentrog, T.: Statistical Characterization of Geographic WiFi Hotspots Distribution, (2014).
  • 1.
    Pfaffenberger, F.: Modelling and Analysis of Social and Temporal Dynamics of YouTube Video Request Processes, (2014).