With the development of mobile computing, location-based services (LBSs) have been developed to provide services based on location information through communication networks or the global positioning system. In recent years, LBSs have evolved into smart LBSs, which provide many services using only location information. These include basic services such as traffic, logistic, and entertainment services. However, a smart LBS may require relatively complicated operations, which may not be effectively performed by the mobile computing system. To overcome this problem, a computation offloading technique can be used to perform certain tasks on mobile devices in cloud and fog environments. Furthermore, mobile platforms exist that provide smart LBSs. The smart cross-platform is a solution based on a virtual machine (VM) that enables compatibility of content in various mobile and smart device environments. However, owing to the nature of the VM-based execution method, the execution performance is degraded compared to that of the native execution method. In this paper, we introduce a computation offloading technique that utilizes fog computing to improve the performance of VMs running on mobile devices. We applied the proposed method to smart devices with a smart VM (SVM) and HTML5 SVM to compare their performances.

We propose a middleware platform built on wireless USB (WUSB) over wireless body area networks (WBAN) hierarchical protocol for wearable health-monitoring systems (WHMS). The proposed middleware platform is composed of time-synchronization and localization solutions. It is executed on the basis of WUSB over WBAN protocol at each wearable sensor node comprising the WHMS. In the platform, firstly, the time-synchronization middleware is executed. After that, a WHMS host calculates the location of a receiving sensor node by using the difference between the times at which the sensor node received different WBAN beacon frames sent from the WHMS host. The WHMS host interprets the status and motion of the wearable body-sensor objects.

Mobile device environment has increased demand for educational resources that can be accessed on and off-campus. The resources such as digital textbooks provide various features, including multimedia, web-based application and annotation functionality, yet a number of usability issues remains for digital textbook to be a useful educational element. Especially, a digital textbook allows a learner to interact with both its contents and even other class members. Therefore, both self-directed and collaborative learning are the most important usability issues, and they have to be considered in use of digital resources. In this paper, we developed annotation interface with tagging functionality which is one of most powerful feature in digital textbooks, and we conducted an evaluation for annotation user interface usability and whether its functionalities are effective and efficient for educational use. To do this, we applied combined and comparative metrics approaches to measure task performance of our system.