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Traffic modeling based on real user-generated data from a wireless service provider

Kastrinakis Marios

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URI: http://purl.tuc.gr/dl/dias/3F1033F3-7AA8-43AB-B536-B71C10601298
Year 2015
Type of Item Diploma Work
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Summary

Nowadays, smart mobile devices tend to replace personal computers, such as desktops and laptops, in daily applications such as internet browsing, emailing, office and basic corporate applications. On the other hand, users still want to use a monitor, keyboard and mouse, as usual, when they are not on the move and the most common way to do that is by using a wireless docking station over a Wi-Fi network. High quality video transmission (for example the desktop view of a smart device) over Wi-Fi networks on heavily loaded environments has been proven problematic in terms of Quality of Service (QoS) and fair bandwidth allocation between users. In this thesis, we developed and tested four different modeling techniques for predicting the volume of video traffic that is generated by an average user’s computer during a day. We propose, for the first time in the relevant literature, to the best of our knowledge, a highly accurate video traffic model that is capable to predict the video frames’ sizes of the specific type of video traffic. Our models can be easily used as source traffic generators in order to facilitate the study of H.264 transmission performance over wireless networks.

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