MyBatRecommender: otimização automatizada do consumo de energia em smartphones Android em nível de software - Cunha, Marcel Popolin de Araújo (2016)
Nowadays smartphones are composed of a wide range of sensors and resources such as GPS (Global Positioning System), Bluetooth and Internet connection through Wi-Fi, 3G, among others resources. Along with the smartphone’s increasing popularity around the world, there is an increasing development and popularity of power-hungry applications: applications that take advantage from these resources and may reduce the smartphones autonomy. This fact is known as one of the biggest to be solved when talking about nowadays smartphones. Considering this, many solutions were proposed and approach this topic in different ways. These solutions can be classified in two major groups: software layer solutions and hardware layer solutions. In one hand, the software layer solutions are the ones that try to reduce the smartphone’s energy drain by only changing the software that composes the smartphone. For example, by improving the Wi-Fi interface or managing the running applications of the smartphone. On the other hand, the hardware layer solutions are the ones that try to improve or increase the energy availability of the smartphone changing or improving only the physical components, for example evolving the technology regarding the batteries. This study presents an approach in software layer for this problem: a system for managing the states of the smartphone’s sensors and components, based on the user profile, aiming energy savings. This work consisted of three steps. In the first step the literature research was done and also a research of the existing solutions in the same area. In the second step the mechanism, called MyBatRecommender, composed by the server and client sides, was presented and developed for the Android operational system. In the last step some validation tests were applied aiming to verify the system efficiency. The results show that when applied to a controlled scenario, the MyBatRecommender achieves around thirty-two per cent of energy savings.