Energy-Efficient Video Streaming in IP Networks

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Dr. Huszák Árpád
Department of Networked Systems and Services

In recent years, the popularity of multimedia services among wired and wireless users has been more and more noticeable. Telecommunication service providers offer higher bitrates in their access networks, besides that the growing number of the different mobile devices (laptop, smartphone and tablet) results an increasing need for multimedia content.

Therefore the consumption of mobile devices has become an important issue. It is relevant even for an ordinary user, that how many hours his/her portable computer or smartphone is able to operate after a full recharging. The capacity of the batteries increases much slower than the consumption of the mobile processors, displays or interfaces. A fully charged battery is able to operate a laptop, smartphone or any other mobile device during less and less time, thereby lots of research aim to decrease the overall consumption of these mobile devices.

Energy efficiency became an important issue in case of live video streaming as well, therefore I develop and introduce a model in my thesis work, which can significantly reduce the energy requirements of playing live media. Longer battery time and environmentally friendly operation can be reachable using my model.

The increasing popularity of IP based multimedia applications causes higher bandwidth usage in both wired and wireless networks. These trends were motivating me to investigate energy efficient solutions for video streaming services. In the first part of my thesis I give an overview about the multimedia services, describing the main container formats and protocols. I introduce some related works on energy-efficient streaming models based on published papers. In the second part of my work I introduce my own model and describe the used architecture and protocols. In order to evaluate the proposed model I perform analytical calculations to examine applicability of the model. Simulation was also performed with the aim of further analysis of the model. Based on the achieved results I study how my model can be adaptable, when more than one client is using it. Finally, I summarize my experiences.


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