“Smart cafe”: A mobile local computing system based on indoor virtual cloud

With network developing and virtualization rising, more and more indoor environment (POIs) such as cafe, library, office, even bus and subway can provide plenty of bandwidth and computing resources. Meanwhile many people daily spending much time in them are still suffering from the mobile device with limited resources. This situation implies a novel local cloud computing paradigm in which mobile device can leverage nearby resources to facilitate task execution. In this paper, we implement a mobile local computing system based on indoor virtual cloud. This system mainly contains three key components: 1) As to application, we create a parser to generate the “method call and cost tree” and analyze it to identify resource-intensive methods. 2) As to mobile device, we design a self-learning execution controller to make offloading decision at runtime. 3) As to cloud, we construct a social scheduling based application-isolation virtual cloud model. The evaluation results demonstrate that our system is effective and efficient by evaluating CPU-intensive calculation application, Memoryintensive image translation application and I/O-intensive image downloading application.