Intern
    Lehrstuhl für Informatik III

    Web portal online!

    19.01.2017

    We are pleased that the web portal for YoMoApp users (YoMoApp Dashboard) is now available. Log into the homepage and download all the information about your YouTube streaming behavior. The goal is to give all interested parties - especially scientists - access to their measurement data and YouTube streaming performance.

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    We are proud that in 2016 we have passed the great threshold of 1500 chats. Thus, we have gained chats and important data, which are used for scientific work. Thanks to all for contributing.

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    We are preparing a download portal for YoMoApp. This will make it possible to retrieve your statistics and download behavior analysis in the future. The idea is that in the future researchers will be able to use the app to retrieve YouTube analysis data on their own.

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    The recent trend towards encrypted HTTPS traffic (e.g., YouTube, Vimeo) is about to inhibit the applicability of passive monitoring in the operators' networks to estimate the QoE of end users. However, machine learning is a promising approach to gain insights into the streaming quality from traffic/flow characteristics.

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    Wenn die Videos auf dem Smartphone ruckeln, stellt sich der Nutzer gerne die Frage, ob er denn den "richtigen" Anbieter hat. Mit einer App wollen Informatiker herausfinden, was die Hauptursachen für schlechtes Streaming sind und welches Netz am besten ist – jeder Androidnutzer kann helfen.

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    YouTube is one of the most popular and volume-dominant services in today’s Internet, and has changed the Web for ever. We have published a research paper with a full manual for the modeling of the YouTube Video Streaming service.

     

    Wamser, F., Casas, P., Seufert, M., Moldovan, C., Tran-Gia, P., Hoßfeld, T.:

    Modeling the YouTube Stack: from Packets to Quality of Experience.

    Computer Networks. (2016).

     

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    YoMoApp (YouTube Performance Monitoring Application), an Android application, which passively monitors key performance indicators (KPIs) of YouTube adaptive video streaming on end-user smartphones. The monitored KPIs (i.e., player state/events, buffer, and video quality level) can be used to analyze the QoE of mobile YouTube video sessions. YoMoApp is a valuable tool to assess the performance of mobile networks with respect to YouTube traffic, as well as to develop optimizationsand QoE models for mobile HTTP adaptive streaming.

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    We implemented WhatsAnalyzer to investigate how group-based communication changes the activity patterns of multiple users. When evaluating communication technologies, models from the past (e.g., Poisson arrival process of end-to-end voice calls) cannot be directly used for nowadays applications (e.g., WhatsApp messages are exchanged in groups of users) and need to be adapted to integrate interaction of users on a smaller time scale. Therefore, we analyze the group communication behavior in WhatsApp and investigate possible implications of this emerging communication paradigm on networking technology.

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    Lehrstuhl für Informatik III (Kommunikationsnetze)
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