Activity recognition and resource optimization in mobile cloud through MapReduce

Mobile cloud computing aims at improving user experience through enhancing the ability of mobile applications by doing intensive tasks in the cloud. In this paper we consider an environment similar to a hybrid cloud in which the mobile device works as a private cloud. Given that the mobile phone has both limited processing resources and battery time, the proposed mobile application architecture has been designed with the capability of sending specified data/parameters to the cloud. This data is subsequently used for further processing/mining and visualization to assist in inferring further information through mapreduce. This information gives details about resource and battery consumption which will help in optimizing the relationship between the mobile device and cloud. It will also be beneficial to the optimization of the mobile application through the trends visualized in the cloud. In this paper we created an activity recognition health application as an example and helped the user about his health along with giving an insight into abnormal behavior and lifestyle trends.