Automatic Optimizer Generation Method Based on Location and Context Information to Improve Mobile Services

Several location-based services (LBSs) have been recently developed for smartphones. Among these are proactive LBSs, which provide services to smartphone users by periodically collecting background logs. However, because they consume considerable battery power, they are not widely used for various LBS-based services. Battery consumption, in particular, is a significant issue on account of the characteristics of mobile systems. This problem involves a greater service restriction when performing complex operations. Therefore, to successfully enable various services based on location, this problem must be solved. In this paper, we introduce a technique to automatically generate a customized service optimizer for each application, service type, and platform using location and situation information. By using the proposed technique, energy and computing resources can be more efficiently employed for each service. Thus, users should receive more effective LBSs on mobile devices, such as smartphones