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Journal of Computer Networks and Communications
Volume 2013 (2013), Article ID 176217, 13 pages
Research Article

Angry Apps: The Impact of Network Timer Selection on Power Consumption, Signalling Load, and Web QoE

Institute of Computer Science, University of Würzburg, Chair of Communication Networks, Am Hubland, 97074 Würzburg, Germany

Received 2 November 2012; Revised 23 January 2013; Accepted 13 February 2013

Academic Editor: Pedro Merino

Copyright © 2013 Christian Schwartz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The popularity of smartphones and mobile applications has experienced a considerable growth during the recent years, and this growth is expected to continue in the future. Since smartphones have only very limited energy resources, battery efficiency is one of the determining factors for a good user experience. Therefore, some smartphones tear down connectionsto the mobile network soon after a completed data transmission to reduce the power consumption of their transmission unit. However, frequent connection reestablishments caused by apps which send or receive small amounts of data often lead to a heavy signalling load within the mobile network. One of the major contributions of this paper is the investigation of the resulting tradeoff between energy consumption at the smartphone and the generated signalling traffic in the mobile network. We explain that this tradeoff can be controlled by the connection release timeout and study the impact of this parameter for a number of popular apps that cover a wide range of traffic characteristics in terms of bandwidth requirements and resulting signalling traffic. Finally, we study the impact of the timer settings on Quality of Experience (QoE) for web traffic. This is an important aspect since connection establishments not only lead to signalling traffic but also increase the load time of web pages.