Communication devices are evolving rapidly, with features that are increasingly complex and require high battery power consumption. Scheduling tasks according to the situation is presented as one of the most promising solutions to meet the needs of smartphone users and maintain the autonomy of these devices. The objective of this project is to create a framework that identifies and defer energetically costly actions when the system reserve is at a lower than expected level and that is able to define when to perform these actions at their maximum performance or in an economical way. When analyzing complete cycles of battery discharge (from 100% to 0%), it is verified that the framework, when in automatic optimization mode, presents an expressive energy saving, which on average is close to 33%. When it is considered a dynamic scenario in which the user can partially recharge the device throughout the day, the economy reaches 91%.