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Despite the advances in battery technologies, mobile phones still suffer from severe energy limitations. Modern handsets are rich devices that can support multitasking thanks to their high processing power and provide a wide range of resources such as sensors and network interfaces with different energy demands. There have been multiple attempts to characterise those energy demands; both to save or to allocate energy to the applications on the handset. However, there is still little understanding on how the interdependencies between resources (interdependencies caused by the applications and users' behaviour) affect the battery life. In this paper, we demonstrate the necessity of considering all those dynamics in order to characterise the energy demands of the system accurately. These results indicate that simple algorithmic and rule-based scheduling techniques [7] are not the most appropriate way of managing the resources since their usage can be affected by contextual factors, making necessary to find customised solutions that consider each user's behaviour and handset features.
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Vallina-Rodríguez et al. (2010) studied this question.
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