Scalable video coding allows an efficient provision of video services at different quality levels with different energy demands. According to the specific type of service and network scenario, end users and/or operators may decide to choose among different energy versus quality combinations. In order to deal with the resulting trade-off, in this paper we analyze the number of video layers that are worth to be received taking into account the energy constraints. A single-objective optimization is proposed based on dynamically selecting the number of layers, which is able to minimize the energy consumption with the constraint of a minimal quality threshold to be reached. However, this approach cannot reflect the fact that the same increment of energy consumption may result in different increments of visual quality. Thus, a multiobjective optimization is proposed and a utility function is defined in order to weight the energy consumption and the visual quality criteria. Finally, since the optimization solving mechanism is computationally expensive to be implemented in mobile devices, a heuristic algorithm is proposed. This way, significant energy consumption reduction will be achieved while keeping reasonable quality levels. 1. Introduction The evolution of multimedia encoding techniques allows efficiently provisioning video services at different quality levels. However, resulting streams lead also to different energy consumptions making it difficult to simultaneously satisfy both energy consumption and quality requirements. Therefore, an energy versus quality compromise solution is commonly required. In commercial cellular networks, users are used to dealing with these trade-offs either manually or automatically (i.e., using small widgets to reduce display brightness, disable radio interfaces, etc.) and normally maintaining the same play-out quality. However, reduced energy consumption becomes a truly severe constraint in specific communication scenarios such as mobile emergency networks or distributed sensors. Additionally, any solution will also depend on the characteristics of the video players although higher resolution video could improve visual quality for high-end mobile devices, for others no visible quality improvement is achieved due to available screen resolution, codecs, or CPU power. So, additional energy consumption, higher data bandwidth, and spectrum use would have no real impact on users satisfaction. Energy- and visual quality-aware video dynamic transmission schemes would allow network operators and users to avoid such waste of
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