A Low Power Lifelog Management Scheme Based on User Movement Behaviors in Wireless Networks

With the ever-improving performance of smartphone cameras and the universal dissemination of cloud services, users can now record and store the events in their daily lives more easily and conveniently. The advent of lifelong technology has been changing the uses as well as the paradigm of internet services, and emphasizing the importance of services being personalization. As the amount of lifelog data becomes vast, it requires an efficient way to manage and store such vast information. In this paper, we propose an low power lifelog management scheme based on user movement behaviors in wireless networks. In order to reduce the power consumption of a smartphone, in our proposal, frequency of data collection and transfer can be dynamically adjusted based on a user's movement pattern. The analytical results show that our approach achieves better performance than that of the existing lifelog management scheme