Praktika

2020

• Hildebrand, K.: Impact of Rendering Times on the Perceived Loading Speed of Web Pages, (2020).
  [ Abstract ]
   
  Contact/Kontakt: michael.seufert@uni-wuerzburg.de Title: Impact of Rendering Times on the Perceived Loading Speed of Web Pages Abstract: The most dominant QoE (Quality of Experience, i.e., subjectively perceived quality) influence factor of web browsing is the page load time. However, pages do not load in a single event, but different parts of the web page are displayed at different rendering times. In this work, a study shall be conducted to investigate the impact of rendering times on the perceived loading speed of web pages. The results of the study shall be evaluated to derive recommendations for networking as well as rendering aspects of web browsing. Titel: Einfluss von Anzeigezeiten auf die wahrgenomme Ladegeschwindigkeit von Webseiten Inhalt: Der wichtigste Einflussfaktor auf die QoE (Quality of Experience, d.h. subjektiv empfundene Dienstgüte) beim Webbrowsing ist die Seitenladezeit. Jedoch laden Webseiten nicht auf einmal, sondern verschiedene Teile der Seite werden zu unterschiedlichen Zeitpunkten angezeigt. In dieser Arbeit soll eine Studie durchgeführt werden, mit der der Einfluss dieser Anzeigezeiten auf die wahrgenommene Ladegeschwindigkeit untersucht werden kann. Die Ergebnisse der Studie sollen ausgewehrtet werden, um Empfehlungen für Netzwerk- und Renderingaspekte beim Webbrowsen abzuleiten.
• Raffeck, S.: Towards Modeling Energy Performance of LoRaWAN Transmissions: A Verification of Theoretical Predictions, (2020).
   

2019

• Stulier, N.: Statistische Evaluation der APM in DOTA 2, (2019).
   
• Janiak, L.: Analysis of Geographic Data in R, (2019).
   
• Biskup, F.: IoT-Datenanalyse im Smart City-Kontext, (2019).
   
• Tönsing, L.: Untersuchung des Einflusses der Anleitungs- und Bearbeitungssprache auf die Ergebnisqualität von Crowdsourcing-Aufgaben, (2019).
   
• Smietanka, O.: Comparison of LPWAN IoT Device Communication Techniques LoRa and NB-IoT, (2019).
   

2018

• Popp, C.: Analysis of WebRTC Video Communications in a Cloud Testbed Setup, (2018).
   
• Steurer, F.: Optimization of Scheduling Mechanisms for Crowdsourcing Tasks Considering Time-dependent System Parameters, (2018).
   

2017

• Knapp, T.: Extending the Monitoring Features of ONOS, (2017).
  [ Abstract ]
   
  The SDN controller ONOS lacks certain network monitoring capabilities. The task is to develop an ONOS application which utilizes the interfaces provided by ONOS and enableds the active measurement of a predefined set of network metrics.
• Kamneng Kwam, B.: Static Placement of Services on Edge Servers, (2017).
   
• Wehner, N.: Unsupervised QoE Field Study for Mobile YouTube Video Streaming with YoMoApp, (2017).
   
• Sommer, M.: Implementation of an OpenFlow Fuzzing Framework, (2017).
   

2016

• Beutel, A.: Correlation of Subjective and Objective Measurements in Enterprise Networks, (2016).
   
• Züfle, M.: Testbed Validation and Comparison with Simulation, (2016).
  [ Abstract ]
   
  In this report the main components of a testbed for evaluating the performance of resource management strategies has been validated. Application-aware resource management is a very important task since high quality applications like video streaming, social networking, and online gaming need a more intelligent bandwidth allocation policy than best effort to reach the highest possible Quality of Experience for all end users. Several tests have been performed to validate the determination of the web page size, Emma, Dory, and TraSh. It has been shown that the web page size has to be determined by measuring the used bandwidth at the router using a tool like ifstat since HTTP and TCP headers are not considered by tools within the browser like Firebug. Additionally, measurements provided that the latency caused by sending the resource allocation commands from Dory to TraSh is very small and should not affect the resource management results. Furthermore, the different random number generator distributions have been examined. It has been shown that Emma typically generates too many request arrivals with too low interarrival time so that requests are rejected. The validation of TraSh has shown that the time needed to realize the resource allocation adaption is pretty short and that there is no statistically significant difference between this delay for different capacities. On top of that, several problems of TraSh have been detected. Finally, the download times of web browsing requests have been measured and compared to simulation results. It has been shown that the download times in the measurement are much higher than the ones of the simulation if there is no initial delay implemented. By implementing an initial delay in the simulation it was shown that the download times converge. However, the initial delay needs to be further investigated since the elapsed time is not reliable known. On top of that, the problems of TraSh need more examination and resolving. Finally, the resource management strategies need to be implemented in Dory in order to measure their impact on download times for web browsing and buffering ratio for video streaming.
• Ott, S.: Browser-based Measurement of HTTP Live Streaming Performance during the Olympic Games 2016, (2016).
   
• Schreck, M.: Matlab REST API, (2016).
   

2015

• Allendorf, F.: Assessing the Accuracy of the NetGraph Network Measurement Tool in Dota 2, (2015).
   
• Müssig, A.: Comparison of the Data Plane Performance of a Commercial Hardware Firewall and its Software Pendant, (2015).
   

2012

• Metter, C.: An Evaluation of Open-Source Cloud Platforms and Analysis of VM-Migration Traffic, (2012).