Abstract
Mobile devices are constrained by the limited capacities of their small Iyatteries. However, profiling the energy consumed in the task execution is crucial to help the developers to build energy efficient applications. Therefore, the major challenge in the profiling approach is to accurately estimating the energy consumed for an application by the hardware components, such as CPU, memory, storage unit, and network interfaces. In this work, we develop and validate hardware and software profiling models and procedures. We profile smartphone CPU, where we consider multi-core CPUs and the impact of Dynamic Voltage and Frequency Scaling mechanism on the power consumption. hi addition, we profile smartplione storage unit by taking into account the writing and reading :rate to the unit. Moreover, we experimentally validated these profiles on two diverse smartphones with different versions of operating systems. The experimental results reveal that our profiles are able to estimate the application energy accurately.