Teaching

Telefon	(0931) 31-88150
Telefax	(0931) 31-86632
E-Mail	nikolas.wehner@informatik.uni-wuerzburg.de
Raum	B208
Anschrift	Lehrstuhl für Informatik III Am Hubland D-97074 Würzburg

Contents: Overview | Publications | Teaching | Working Group | Projects

Supervised Theses

Hofmann, J.: Deep Reinforcement Learning for Configuration of Time-Sensitive-Networking, (2020).

[ BibTeX ] [ EndNote ]

@mastersthesis{info3-bachelor-2020-8, author = {Hofmann, Jan}, keywords = {myown sys:hidden:bachelor sys:hidden:completed sys:hidden:supervisor:michael.seufert sys:hidden:supervisor:alexej.grigorjew sys:hidden:supervisor:nikolas.wehner kikdin ucn}, month = 7, school = {University of Würzburg}, title = {Deep Reinforcement Learning for Configuration of Time-Sensitive-Networking}, year = 2020 }

%0 Thesis %1 info3-bachelor-2020-8 %A Hofmann, Jan %D 2020 %T Deep Reinforcement Learning for Configuration of Time-Sensitive-Networking
Fehler, H.: Comparison of Web QoE Algorithms on Different Devices, (2020).

[ Abstract ] [ BibTeX ] [ EndNote ]

Contact/Kontakt: nikolas.wehner@informatik.uni-wuerzburg.de Impairments in the Web QoE, e.g., low page load times, can lead to annoyed users which in the end can result in revenue losses for companies. In literature, several algorithm exist for predicting the Web QoE, e.g. Speed Index, Above the Fold, etc. Based on data from a measurement study, these algorithms shall be evaluated and compared in this work. In particular, a comparison of the metrics among the devices (Smartphone, Tablet, Desktop PC), which were used to generate the measurement data, is of interest.

@mastersthesis{info3-bachelor-2019-19, abstract = {Contact/Kontakt: nikolas.wehner@informatik.uni-wuerzburg.de Impairments in the Web QoE, e.g., low page load times, can lead to annoyed users which in the end can result in revenue losses for companies. In literature, several algorithm exist for predicting the Web QoE, e.g. Speed Index, Above the Fold, etc. Based on data from a measurement study, these algorithms shall be evaluated and compared in this work. In particular, a comparison of the metrics among the devices (Smartphone, Tablet, Desktop PC), which were used to generate the measurement data, is of interest.}, author = {Fehler, Helena}, keywords = {myown sys:hidden:bachelor sys:hidden:completed sys:hidden:supervisor:nikolas.wehner ucn}, school = {University of Würzburg}, title = {Comparison of Web QoE Algorithms on Different Devices}, year = 2020 }

%0 Thesis %1 info3-bachelor-2019-19 %A Fehler, Helena %D 2020 %T Comparison of Web QoE Algorithms on Different Devices %X Contact/Kontakt: nikolas.wehner@informatik.uni-wuerzburg.de Impairments in the Web QoE, e.g., low page load times, can lead to annoyed users which in the end can result in revenue losses for companies. In literature, several algorithm exist for predicting the Web QoE, e.g. Speed Index, Above the Fold, etc. Based on data from a measurement study, these algorithms shall be evaluated and compared in this work. In particular, a comparison of the metrics among the devices (Smartphone, Tablet, Desktop PC), which were used to generate the measurement data, is of interest.
Mertinat, N.: Impact of Content Selection on Crowdsourced QoE Studies of HTTP Adaptive Streaming on Mobile Devices, (2020).

[ BibTeX ] [ EndNote ]

@mastersthesis{info3-bachelor-2019-5, author = {Mertinat, Nils}, keywords = {myown sys:hidden:bachelor sys:hidden:completed sys:hidden:supervisor:michael.seufert sys:hidden:supervisor:nikolas.wehner ucn}, month = 2, school = {University of Würzburg}, title = {Impact of Content Selection on Crowdsourced QoE Studies of HTTP Adaptive Streaming on Mobile Devices}, year = 2020 }

%0 Thesis %1 info3-bachelor-2019-5 %A Mertinat, Nils %D 2020 %T Impact of Content Selection on Crowdsourced QoE Studies of HTTP Adaptive Streaming on Mobile Devices

Seminar Talks

SS 20

Internet Access in High Speed Trains

WS 19/20

QoE Monitoring of Internet Applications
QoE Monitoring from Encrypted Internet Traffic

Supervised Theses

Seminar Talks

Hinweis zum Datenschutz

Hinweis zum Datenschutz

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